The role of large pedigrees in an era of high-throughput sequencing

Shared genomic segments analysis identifies MHC class I and class III molecules as genetic risk factors for juvenile idiopathic arthritis

Juvenile idiopathic arthritis (JIA) is a complex rheumatic disease encompassing several clinically defined subtypes of varying severity. The etiology of JIA remains largely unknown, but genome-wide association studies (GWASs) have identified up to 22 genes associated with JIA susceptibility, including a well-established association with HLA-DRB1. Continued investigation of heritable risk factors has been hindered by disease heterogeneity and low disease prevalence. In this study, we utilized shared genomic segments (SGS) analysis on whole-genome sequencing of 40 cases from 12 multi-generational pedigrees significantly enriched for JIA. Subsets of cases are connected by a common ancestor in large extended pedigrees, increasing the power to identify disease-associated loci. SGS analysis identifies genomic segments shared among disease cases that are likely identical by descent and anchored by a disease locus. This approach revealed statistically significant signals for major histocompatibility complex (MHC) class I and class III alleles, particularly HLA-A∗02:01, which was observed at a high frequency among cases. Furthermore, we identified an additional risk locus at 12q23.2-23.3, containing genes primarily expressed by naive B cells, natural killer cells, and monocytes. The recognition of additional risk beyond HLA-DRB1 provides a new perspective on immune cell dynamics in JIA. These findings contribute to our understanding of JIA and may guide future research and therapeutic strategies.

A Rare Variant in MDH2 (rs111879470) Is Associated with Predisposition to Recurrent Breast Cancer in an Extended High-Risk Pedigree

A significant fraction of breast cancer recurs, with lethal outcome, but specific genetic variants responsible have yet to be identified. Five cousin pairs with recurrent breast cancer from pedigrees with a statistical excess of recurrent breast cancer were sequenced to identify rare, shared candidate predisposition variants. The candidates were tested for association with breast cancer risk with UKBiobank data. Additional breast cancer cases were assayed for a subset of candidate variants to test for co-segregation. Three-dimensional protein structure prediction methods were used to investigate how the mutation under consideration is predicted to change structural and electrostatic properties in the mutated protein. One hundred and eighty-one rare candidate predisposition variants were shared in at least one cousin pair from a high-risk pedigree. A rare variant in MDH2 was found to segregate with breast-cancer-affected relatives in one extended pedigree. MDH2 is an estrogen-stimulated gene encoding the protein malate dehydrogenase, which catalyzes the reversible oxidation of malate to oxaloacetate. The molecular simulation results strongly suggest that the mutation changes the NAD+ binding pocket electrostatics of MDH2. This small sequencing study, using a powerful approach based on recurrent breast cancer cases from high-risk pedigrees, identified a set of strong candidate variants for inherited predisposition for breast cancer recurrence, including MDH2, which should be pursued in other resources.

Familial Associations of Prevalence and Cause-Specific Mortality for Thoracic Aortic Disease and Bicuspid Aortic Valve in a Large-Population Database

BACKGROUND

Thoracic aortic disease and bicuspid aortic valve (BAV) likely have a heritable component, but large population-based studies are lacking. This study characterizes familial associations of thoracic aortic disease and BAV, as well as cardiovascular and aortic-specific mortality, among relatives of these individuals in a large-population database.

METHODS

In this observational case-control study of the Utah Population Database, we identified probands with a diagnosis of BAV, thoracic aortic aneurysm, or thoracic aortic dissection. Age- and sex-matched controls (10:1 ratio) were identified for each proband. First-degree relatives, second-degree relatives, and first cousins of probands and controls were identified through linked genealogical information. Cox proportional hazard models were used to quantify the familial associations for each diagnosis. We used a competing-risk model to determine the risk of cardiovascular-specific and aortic-specific mortality for relatives of probands.

RESULTS

The study population included 3 812 588 unique individuals. Familial hazard risk of a concordant diagnosis was elevated in the following populations compared with controls: first-degree relatives of patients with BAV (hazard ratio [HR], 6.88 [95% CI, 5.62-8.43]); first-degree relatives of patients with thoracic aortic aneurysm (HR, 5.09 [95% CI, 3.80-6.82]); and first-degree relatives of patients with thoracic aortic dissection (HR, 4.15 [95% CI, 3.25-5.31]). In addition, the risk of aortic dissection was higher in first-degree relatives of patients with BAV (HR, 3.63 [95% CI, 2.68-4.91]) and in first-degree relatives of patients with thoracic aneurysm (HR, 3.89 [95% CI, 2.93-5.18]) compared with controls. Dissection risk was highest in first-degree relatives of patients who carried a diagnosis of both BAV and aneurysm (HR, 6.13 [95% CI, 2.82-13.33]). First-degree relatives of patients with BAV, thoracic aneurysm, or aortic dissection had a higher risk of aortic-specific mortality (HR, 2.83 [95% CI, 2.44-3.29]) compared with controls.

CONCLUSIONS

Our results indicate that BAV and thoracic aortic disease carry a significant familial association for concordant disease and aortic dissection. The pattern of familiality is consistent with a genetic cause of disease. Furthermore, we observed higher risk of aortic-specific mortality in relatives of individuals with these diagnoses. This study provides supportive evidence for screening in relatives of patients with BAV, thoracic aneurysm, or dissection.

Employing pigs to decipher the host genetic effect on gut microbiome: advantages, challenges, and perspectives

The gut microbiota is a complex and diverse ecosystem comprised of trillions of microbes and plays an essential role in host's immunity, metabolism, and even behaviors. Environmental and host factors drive the huge variations in the gut microbiome among individuals. Here, we summarize accumulated evidences about host genetic effect on the gut microbial compositions with emphases on the correlation between host genetic kinship and the similarity of microbial compositions, heritability estimates of microbial taxa, and identification of genomic variants associated with the gut microbiome in pigs as well as in humans. A proportion of bacterial taxa have been reported to be heritable, and numerous variants associated with the diversity of the gut microbiota or specific taxa have been identified in both humans and pigs. LCT and ABO gene have been replicated in multiple studies, and its mechanism have been elucidated clearly. We also discuss the main advantages and challenges using pigs as experimental animals in exploring host genetic effect on the gut microbial composition and provided our insights on the perspectives in this area.

Deconstructing a Syndrome: Genomic Insights Into PCOS Causal Mechanisms and Classification

Polycystic ovary syndrome (PCOS) is among the most common disorders in women of reproductive age, affecting up to 15% worldwide, depending on the diagnostic criteria. PCOS is characterized by a constellation of interrelated reproductive abnormalities, including disordered gonadotropin secretion, increased androgen production, chronic anovulation, and polycystic ovarian morphology. It is frequently associated with insulin resistance and obesity. These reproductive and metabolic derangements cause major morbidities across the lifespan, including anovulatory infertility and type 2 diabetes (T2D). Despite decades of investigative effort, the etiology of PCOS remains unknown. Familial clustering of PCOS cases has indicated a genetic contribution to PCOS. There are rare Mendelian forms of PCOS associated with extreme phenotypes, but PCOS typically follows a non-Mendelian pattern of inheritance consistent with a complex genetic architecture, analogous to T2D and obesity, that reflects the interaction of susceptibility genes and environmental factors. Genomic studies of PCOS have provided important insights into disease pathways and have indicated that current diagnostic criteria do not capture underlying differences in biology associated with different forms of PCOS. We provide a state-of-the-science review of genetic analyses of PCOS, including an overview of genomic methodologies aimed at a general audience of non-geneticists and clinicians. Applications in PCOS will be discussed, including strengths and limitations of each study. The contributions of environmental factors, including developmental origins, will be reviewed. Insights into the pathogenesis and genetic architecture of PCOS will be summarized. Future directions for PCOS genetic studies will be outlined.

Open problems in human trait genetics

Genetic studies of human traits have revolutionized our understanding of the variation between individuals, and yet, the genetics of most traits is still poorly understood. In this review, we highlight the major open problems that need to be solved, and by discussing these challenges provide a primer to the field. We cover general issues such as population structure, epistasis and gene-environment interactions, data-related issues such as ancestry diversity and rare genetic variants, and specific challenges related to heritability estimates, genetic association studies, and polygenic risk scores. We emphasize the interconnectedness of these problems and suggest promising avenues to address them.

Involvement of Rare Mutations of SCN9A, DPP4, ABCA13, and SYT14 in Schizophrenia and Bipolar Disorder

Rare mutations associated with schizophrenia (SZ) and bipolar disorder (BD) usually have high clinical penetrance; however, they are highly heterogeneous and personalized. Identifying rare mutations is instrumental in making the molecular diagnosis, understanding the pathogenesis, and providing genetic counseling for the affected individuals and families. We conducted whole-genome sequencing analysis in two multiplex families with the dominant inheritance of SZ and BD. We detected a G327E mutation of SCN9A and an A654V mutation of DPP4 cosegregating with SZ and BD in one three-generation multiplex family. We also identified three mutations cosegregating with SZ and BD in another two-generation multiplex family, including L711S of SCN9A, M4554I of ABCA13, and P159L of SYT14. These five missense mutations were rare and deleterious. Mutations of SCN9A have initially been reported to cause congenital insensitivity to pain and neuropathic pain syndromes. Further studies showed that rare mutations of SCN9A were associated with seizure and autism spectrum disorders. Our findings suggest that SZ and BD might also be part of the clinical phenotype spectra of SCN9A mutations. Our study also indicates the oligogenic involvement in SZ and BD and supports the multiple-hit model of SZ and BD.

Identification of a Rare Novel KMT2C Mutation That Presents with Schizophrenia in a Multiplex Family

Schizophrenia is a complex genetic disorder involving many common variants with modest effects and rare mutations with high penetrance. Rare mutations associated with schizophrenia are highly heterogeneous and private for affected individuals and families. Identifying such mutations can help establish the molecular diagnosis, elucidate the pathogenesis, and provide helpful genetic counseling for affected patients and families. We performed a whole-exome sequencing analysis to search for rare pathogenic mutations co-segregating with schizophrenia transmitted in a dominant inheritance in a two-generation multiplex family. We identified a rare missense mutation H1574R (Histidine1574Arginine, rs199796552) of KMT2C (lysine methyltransferase 2C) co-segregating with affected members in this family. The mutation is a novel deleterious mutation of KMT2C, not reported before in the literature. The KMT2C encodes a histone 3 lysine 4 (H3K4)-specific methyltransferase and involves epigenetic regulation of brain gene expression. Mutations of KMT2C have been found in neurodevelopmental disorders, such as Kleefstra syndrome, intellectual disability, and autism spectrum disorders. Our finding suggests that schizophrenia might be one of the clinical phenotype spectra of KMT2C mutations, and KMT2C might be a novel risk gene for schizophrenia. Nevertheless, the co-segregation of this mutation with schizophrenia in this family might also be due to chance; functional assays of this mutation are needed to address this issue.

The effect of sodium channels on neurological/neuronal disorders: A systematic review

Neurological and neuronal disorders are associated with structural, biochemical, or electrical abnormalities in the nervous system. Many neurological diseases have not yet been discovered. Interventions used for the treatment of these disorders include avoidance measures, lifestyle changes, physiotherapy, neurorehabilitation, pain management, medication, and surgery. In the sodium channelopathies, alterations in the structure, expression, and function of voltage-gated sodium channels (VGSCs) are considered as the causes of neurological and neuronal diseases. Online databases, including Scopus, Science Direct, Google Scholar, and PubMed were assessed for studies published between 1977 and 2020 using the keywords of review, sodium channels blocker, neurological diseases, and neuronal diseases. VGSCs consist of one α subunit and two β subunits. These subunits are known to regulate the gating kinetics, functional characteristics, and localization of the ion channel. These channels are involved in cell migration, cellular connections, neuronal pathfinding, and neurite outgrowth. Through the VGSC, the action potential is triggered and propagated in the neurons. Action potentials are physiological functions and passage of impermeable ions. The electrophysiological properties of these channels and their relationship with neurological and neuronal disorders have been identified. Subunit mutations are involved in the development of diseases, such as epilepsy, multiple sclerosis, autism, and Alzheimer's disease. Accordingly, we conducted a review of the link between VGSCs and neurological and neuronal diseases. Also, novel therapeutic targets were introduced for future drug discoveries.

Analysis of high-risk pedigrees identifies 11 candidate variants for Alzheimer's disease

Introduction

Analysis of sequence data in high‐risk pedigrees is a powerful approach to detect rare predisposition variants.

Methods

Rare, shared candidate predisposition variants were identified from exome sequencing 19 Alzheimer's disease (AD)‐affected cousin pairs selected from high‐risk pedigrees. Variants were further prioritized by risk association in various external datasets. Candidate variants emerging from these analyses were tested for co‐segregation to additional affected relatives of the original sequenced pedigree members.

Results

AD‐affected high‐risk cousin pairs contained 564 shared rare variants. Eleven variants spanning 10 genes were prioritized in external datasets: rs201665195 (ABCA7), and rs28933981 (TTR) were previously implicated in AD pathology; rs141402160 (NOTCH3) and rs140914494 (NOTCH3) were previously reported; rs200290640 (PIDD1) and rs199752248 (PIDD1) were present in more than one cousin pair; rs61729902 (SNAP91), rs140129800 (COX6A2, AC026471), and rs191804178 (MUC16) were not present in a longevity cohort; and rs148294193 (PELI3) and rs147599881 (FCHO1) approached significance from analysis of AD‐related phenotypes. Three variants were validated via evidence of co‐segregation to additional relatives (PELI3, ABCA7, and SNAP91).

Discussion

These analyses support ABCA7 and TTR as AD risk genes, expand on previously reported NOTCH3 variant identification, and prioritize seven additional candidate variants.

An intronic variant in the CELF4 gene is associated with risk for colorectal cancer

BACKGROUND

Germline predisposition variants associated with colorectal cancer (CRC) have been identified but all are not yet identified. We sought to identify the responsible predisposition germline variant in an extended high-risk CRC pedigree that exhibited evidence of linkage to the 18q12.2 region (TLOD = +2.81).

METHODS

DNA from two distantly related carriers of the hypothesized predisposition haplotype on 18q12.2 was sequenced to identify candidate variants. The candidate rare variants shared by the related sequenced subjects were screened in 3,094 CRC cases and 5x population-matched controls from UKBiobank to test for association. Further segregation of the variant was tested via Taqman assay in other sampled individuals in the pedigree.

RESULTS

Analysis of whole genome sequence data for the two related hypothesized predisposition haplotype carriers, restricted to the shared haplotype boundaries, identified multiple (n = 6) rare candidate non-coding variants that were tested for association with CRC risk in UKBiobank. A rare intronic variant ofCELF4 gene, rs568643870, was significantly associated with CRC (p = 0.004, OR = 5.0), and segregated with CRC in other members of the linked pedigree.

CONCLUSION

Evidence of segregation in a high-risk pedigree, case-control association in an external dataset, and identification of additional CRC-affected carriers in the linked pedigree support a role for a rareCELF4 intronic variant in CRC risk.

A Rare Variant in ERF (rs144812092) Predisposes to Prostate and Bladder Cancers in an Extended Pedigree

Simple Summary

Here we applied a powerful predisposition candidate gene identification strategy to identify rare variants shared by two related bladder cancer cases who were members of pedigrees exhibiting a significant excess of bladder cancers. We sequenced the exomes of pairs of related bladder cancer cases belonging to high-risk bladder cancer pedigrees to identify rare, shared variants shared as candidates for predisposition. A rare, shared variant in ERF was also found to show significant association with bladder cancer risk in an independent population, was present in other prostate cancer-affected members in the pedigree, and showed evidence for altering the function of the associated protein. This evidence supports ERF (ETS2 Repressor Factor) as a bladder and prostate cancer predisposition gene.

Abstract

Pairs of related bladder cancer cases who belong to pedigrees with an excess of bladder cancer were sequenced to identify rare, shared variants as candidate predisposition variants. Candidate variants were tested for association with bladder cancer risk. A validated variant was assayed for segregation to other related cancer cases, and the predicted protein structure of this variant was analyzed. This study of affected bladder cancer relative pairs from high-risk pedigrees identified 152 bladder cancer predisposition candidate variants. One variant in ERF (ETS Repressing Factor) was significantly associated with bladder cancer risk in an independent population, was observed to segregate with bladder and prostate cancer in relatives, and showed evidence for altering the function of the associated protein. This finding of a rare variant in ERF that is strongly associated with bladder and prostate cancer risk in an extended pedigree both validates ERF as a cancer predisposition gene and shows the continuing value of analyzing affected members of high-risk pedigrees to identify and validate rare cancer predisposition variants.

Genome-wide analysis of high-risk primary brain cancer pedigrees identifies PDXDC1 as a candidate brain cancer predisposition gene

BACKGROUND

There is evidence for an inherited contribution to primary brain cancer. Linkage analysis of high-risk brain cancer pedigrees has identified candidate regions of interest in which brain cancer predisposition genes are likely to reside.

METHODS

Genome-wide linkage analysis was performed in a unique set of 11 informative, extended, high-risk primary brain cancer pedigrees identified in a population genealogy database, which include from 2 to 6 sampled, related primary brain cancer cases. Access to formalin-fixed paraffin embedded tissue samples archived in a biorepository allowed analysis of extended pedigrees.

RESULTS

Individual high-risk pedigrees were singly informative for linkage at multiple regions. Suggestive evidence for linkage was observed on chromosomes 2, 3, 14, and 16. The chromosome 16 region in particular contains a promising candidate gene, pyridoxal-dependent decarboxylase domain-containing 1 (PDXDC1), with prior evidence for involvement with glioblastoma from other previously reported experimental settings, and contains the lead single nucleotide polymorphism (rs3198697) from the linkage analysis of the chromosome 16 region.

CONCLUSIONS

Pedigrees with a statistical excess of primary brain cancers have been identified in a unique genealogy resource representing the homogeneous Utah population. Genome-wide linkage analysis of these pedigrees has identified a potential candidate predisposition gene, as well as multiple candidate regions that could harbor predisposition loci, and for which further analysis is suggested.

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

BACKGROUND

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

METHODS

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

RESULTS

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

LIMITATIONS

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

CONCLUSION

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

Next Generation Sequencing and Bioinformatics Analysis of Family Genetic Inheritance

Mendelian and complex genetic trait diseases continue to burden and affect society both socially and economically. The lack of effective tests has hampered diagnosis thus, the affected lack proper prognosis. Mendelian diseases are caused by genetic mutations in a singular gene while complex trait diseases are caused by the accumulation of mutations in either linked or unlinked genomic regions. Significant advances have been made in identifying novel diseases associated mutations especially with the introduction of next generation and third generation sequencing. Regardless, some diseases are still without diagnosis as most tests rely on SNP genotyping panels developed from population based genetic analyses. Analysis of family genetic inheritance using whole genomes, whole exomes or a panel of genes has been shown to be effective in identifying disease-causing mutations. In this review, we discuss next generation and third generation sequencing platforms, bioinformatic tools and genetic resources commonly used to analyze family based genomic data with a focus on identifying inherited or novel disease-causing mutations. Additionally, we also highlight the analytical, ethical and regulatory challenges associated with analyzing personal genomes which constitute the data used for family genetic inheritance.

Using Drosophila to drive the diagnosis and understand the mechanisms of rare human diseases

Next-generation sequencing has greatly accelerated the discovery of rare human genetic diseases. Nearly 45% of patients have variants associated with known diseases but the unsolved cases remain a conundrum. Moreover, causative mutations can be difficult to pinpoint because variants frequently map to genes with no previous disease associations and, often, only one or a few patients with variants in the same gene are identified. Model organisms, such as Drosophila, can help to identify and characterize these new disease-causing genes. Importantly, Drosophila allow quick and sophisticated genetic manipulations, permit functional testing of human variants, enable the characterization of pathogenic mechanisms and are amenable to drug tests. In this Spotlight, focusing on microcephaly as a case study, we highlight how studies of human genes in Drosophila have aided our understanding of human genetic disorders, allowing the identification of new genes in well-established signaling pathways.

Segregating patterns of copy number variations in extended autism spectrum disorder (ASD) pedigrees

Autism spectrum disorder (ASD) is a relatively common childhood onset neurodevelopmental disorder with a complex genetic etiology. While progress has been made in identifying the de novo mutational landscape of ASD, the genetic factors that underpin the ASD's tendency to run in families are not well understood. In this study, nine extended pedigrees each with three or more individuals with ASD, and others with a lesser autism phenotype, were phenotyped and genotyped in an attempt to identify heritable copy number variants (CNVs). Although these families have previously generated linkage signals, no rare CNV segregated with these signals in any family. A small number of clinically relevant CNVs were identified. Only one CNV was identified that segregated with ASD phenotype; namely, a duplication overlapping DLGAP2 in three male offspring each with an ASD diagnosis. This gene encodes a synaptic scaffolding protein, part of a group of proteins known to be pathologically implicated in ASD. On the whole, however, the heritable nature of ASD in the families studied remains poorly understood.

SimRVSequences: an R package to simulate genetic sequence data for pedigrees

SUMMARY

We present the R package SimRVSequences to simulate sequence data for pedigrees. SimRVSequences allows for simulations of large numbers of single-nucleotide variants (SNVs) and scales well with increasing numbers of pedigrees. Users provide a sample of pedigrees and SNV data from a sample of unrelated individuals.

AVAILABILITY AND IMPLEMENTATION

SimRVSequences is publicly-available on CRAN https://cran.r-project.org/web/packages/SimRVSequences/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

In-silico profiling and structural insights into the impact of nSNPs in the P. falciparum acetyl-CoA transporter gene to understand the mechanism of drug resistance in malaria

The continuous emergence of resistance to the available drugs poses major constraints in the development of effective therapeutics against malaria. Malaria drug resistance has been attributed to be the manifestation of numerous factors. For example, mutations in the parasite transporter protein acetyl-CoA transporter (Pfact) can remarkably affect its uptake affinity for a drug molecule against malaria, and hence enhance its susceptibility to resistance. To identify major contributors to its loss of functionality, we have thoroughly scrutinized eight such recently reported resistant mutants, via in-silico tools in terms of alterations in different properties. We performed molecular dynamics simulations of the selected Pfact mutants to gain deeper insights into the structural perturbation and dynamicity. Comparison of residue interaction network map of mutants with that of Wild type (WT) protein suggests structural changes as a result of the mutation(s) that translate into the weakening of intra-protein interactions, especially around the drug binding pocket. This, in turn, diminishes the affinity of drug molecules towards the binding site, which was validated by docking analysis. Finally, collating all the observations, we have delineated R108K mutant to deviate the most from WT protein, which, intriguingly suggests that replacing an amino acid with another of similar nature can even translate into greater functional effects as those with dissimilar substitutions.Communicated by Ramaswamy H. Sarma.

ONETOOL for the analysis of family-based big data

Motivation

Despite the need for separate tools to analyze family-based data, there are only a handful of tools optimized for family-based big data compared to the number of tools available for analyzing population-based data.

Results

ONETOOL implements the properties of well-known existing family data analysis tools and recently developed methods in a computationally efficient manner, and so is suitable for analyzing the vast amount of variant data available from sequencing family members, providing a rich choice of analysis methods for big data on families.

Availability and implementation

ONETOOL is freely available from http://healthstat.snu.ac.kr/software/onetool/.

Supplementary information

Supplementary data are available at Bioinformatics online.

GIGI-Quick: a fast approach to impute missing genotypes in genome-wide association family data

Summary

Genome-wide association studies have become common over the last ten years, with a shift towards targeting rare variants, especially in pedigree-data. Despite lower costs, sequencing for rare variants still remains expensive. To have a relatively large sample with acceptable cost, imputation approaches may be used, such as GIGI for pedigree data. GIGI is an imputation method that handles large pedigrees and is particularly good for rare variant imputation. GIGI requires a subset of individuals in a pedigree to be fully sequenced, while other individuals are sequenced only at relevant markers. The imputation will infer the missing genotypes at untyped markers. Running GIGI on large pedigrees for large numbers of markers can be very time consuming. We present GIGI-Quick as a method to efficiently split GIGI's input, run GIGI in parallel and efficiently merge the output to reduce the runtime with the number of cores. This allows obtaining imputation results faster, and therefore all subsequent association analyses.

Availability and and implementation

GIGI-Quick is open source and publicly available via: https://cse-git.qcri.org/Imputation/GIGI-Quick.

Contact

msaad@hbku.edu.qa.

Supplementary information

Supplementary data are available at Bioinformatics online.

Association between polymorphism rs2032487 in the non-muscle myosin heavy chain IIA gene (MHY9) and chronic kidney disease secondary to type 2 diabetes mellitus in a population of the Canary Islands

INTRODUCTION

Certain polymorphisms in the non-muscle myosin IIA (MYH9) and apolipoprotein L1 (APOL1) genes have been associated to chronic kidney disease (CKD) in different populations. This study examined the association between the MHY9 rs2032487 and APOL1 rs73885319 polymorphisms and advanced CKD related to type 2 diabetes mellitus (T2DM) in a population of Gran Canaria (Canary Islands, Spain).

PATIENTS AND METHODS

Polymorphisms were genotyped in 152 patients with advanced CKD (estimated glomerular filtration rate [eGFR]<30mL/min/1.73 m²) secondary to T2DM, 110 patients with T2DM onset ≥ 20 years before without advanced CKD (eGFR ≥ 45mL/min/1.73 m² and no proteinuria), and 292 healthy blood donors over 50 years of age without CKD or diabetes.

RESULTS

The frequency of the risk allele for rs2032487 was 10.7% in patients with diabetes and advanced CKD, 7.1% in those with diabetes but without advanced CKD, and 6.1% in healthy subjects, with significant differences between the first and third groups (P=.015). Among subjects with advanced CKD, 78.5% were homozygous for the protective allele, as compared to 87.9% in the other two groups (P=.015 and P=.016 respectively). The frequency of the risk allele for the rs73885319 polymorphism did not exceed 0.5% in any of the three groups.

CONCLUSIONS

These data suggest that polymorphism rs2032487 is associated to advanced CKD related to T2DM in the population of Gran Canaria.

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.

Association score testing for rare variants and binary traits in family data with shared controls

Genome-wide association studies have been an important approach used to localize trait loci, with primary focus on common variants. The multiple rare variant-common disease hypothesis may explain the missing heritability remaining after accounting for identified common variants. Advances of sequencing technologies with their decreasing costs, coupled with methodological advances in the context of association studies in large samples, now make the study of rare variants at a genome-wide scale feasible. The resurgence of family-based association designs because of their advantage in studying rare variants has also stimulated more methods development, mainly based on linear mixed models (LMMs). Other tests such as score tests can have advantages over the LMMs, but to date have mainly been proposed for single-marker association tests. In this article, we extend several score tests (χcorrected2, WQLS, and SKAT) to the multiple variant association framework. We evaluate and compare their statistical performances relative with the LMM. Moreover, we show that three tests can be cast as the difference between marker allele frequencies (AFs) estimated in each of the group of affected and unaffected subjects. We show that these tests are flexible, as they can be based on related, unrelated or both related and unrelated subjects. They also make feasible an increasingly common design that only sequences a subset of affected subjects (related or unrelated) and uses for comparison publicly available AFs estimated in a group of healthy subjects. Finally, we show the great impact of linkage disequilibrium on the performance of all these tests.

Comparison and assessment of family- and population-based genotype imputation methods in large pedigrees

Genotype imputation is widely used in genome-wide association studies to boost variant density, allowing increased power in association testing. Many studies currently include pedigree data due to increasing interest in rare variants coupled with the availability of appropriate analysis tools. The performance of population-based (subjects are unrelated) imputation methods is well established. However, the performance of family- and population-based imputation methods on family data has been subject to much less scrutiny. Here, we extensively compare several family- and population-based imputation methods on family data of large pedigrees with both European and African ancestry. Our comparison includes many widely used family- and population-based tools and another method, Ped_Pop, which combines family- and population-based imputation results. We also compare four subject selection strategies for full sequencing to serve as the reference panel for imputation: GIGI-Pick, ExomePicks, PRIMUS, and random selection. Moreover, we compare two imputation accuracy metrics: the Imputation Quality Score and Pearson's correlation R ² for predicting power of association analysis using imputation results. Our results show that (1) GIGI outperforms Merlin; (2) family-based imputation outperforms population-based imputation for rare variants but not for common ones; (3) combining family- and population-based imputation outperforms all imputation approaches for all minor allele frequencies; (4) GIGI-Pick gives the best selection strategy based on the R ² criterion; and (5) R ² is the best measure of imputation accuracy. Our study is the first to extensively evaluate the imputation performance of many available family- and population-based tools on the same family data and provides guidelines for future studies.

A Nonsynonymous Variant in the GOLM1 Gene in Cutaneous Malignant Melanoma

Background

Statistically significant linkage of melanoma to chromosome 9q21 was previously reported in a Danish pedigree resource and independently confirmed in Utah high-risk pedigrees, indicating strong evidence that this region contains a melanoma predisposition gene.

Methods

Whole-exome sequencing of pairs of related melanoma case subjects from two pedigrees with evidence of 9q21 linkage was performed to identify the responsible predisposition gene. Candidate variants were tested for association with melanoma in an independent set of 454 unrelated familial melanoma case subjects and 396 unrelated cancer-free control subjects from Utah, and 1534 melanoma case subjects and 1146 noncancer control subjects from Texas (MD Anderson) via a two-sided Fisher exact test.

Results

A rare nonsynonymous variant in Golgi Membrane Protein 1 (GOLM1), rs149739829, shared in two hypothesized predisposition carriers in one linked pedigree was observed. Segregation of this variant in additional affected relatives of the index carriers was confirmed. A statistically significant excess of carriers of the variant was observed among Utah case subjects and control subjects (odds ratio [OR] = 9.81, 95% confidence interval [CI] = 8.35 to 11.26, P < .001) and statistically significantly confirmed in Texas case subjects and control subjects (OR = 2.45, 95% CI = 1.65 to 3.25, P = .02).

Conclusion

These findings support GOLM1 as a candidate melanoma predisposition gene.

Simulating pedigrees ascertained for multiple disease-affected relatives

Background

Studies that ascertain families containing multiple relatives affected by disease can be useful for identification of causal, rare variants from next-generation sequencing data.

Results

We present the R package SimRVPedigree, which allows researchers to simulate pedigrees ascertained on the basis of multiple, affected relatives. By incorporating the ascertainment process in the simulation, SimRVPedigree allows researchers to better understand the within-family patterns of relationship amongst affected individuals and ages of disease onset.

Conclusions

Through simulation, we show that affected members of a family segregating a rare disease variant tend to be more numerous and cluster in relationships more closely than those for sporadic disease. We also show that the family ascertainment process can lead to apparent anticipation in the age of onset. Finally, we use simulation to gain insight into the limit on the proportion of ascertained families segregating a causal variant. SimRVPedigree should be useful to investigators seeking insight into the family-based study design through simulation.

Electronic supplementary material

The online version of this article (10.1186/s13029-018-0069-6) contains supplementary material, which is available to authorized users.

A genome-wide linkage study of autism spectrum disorder and the broad autism phenotype in extended pedigrees

BACKGROUND

Although several genetic variants for autism spectrum disorder (ASD) have now been identified, these largely occur sporadically or are de novo. Much less progress has been made in identifying inherited variants, even though the disorder itself is familial in the majority of cases. The objective of this study was to identify chromosomal regions that harbor inherited variants increasing the risk for ASD using an approach that examined both ASD and the broad autism phenotype (BAP) among a unique sample of extended pedigrees.

METHODS

ASD and BAP were assessed using standardized tools in 28 pedigrees from Canada and the USA, each with at least three ASD-diagnosed individuals from two nuclear families. Genome-wide linkage analysis was performed using the posterior probability of linkage (PPL) statistic, a quasi-Bayesian method that provides strength of evidence for or against linkage in an essentially model-free manner, with outcomes on the probability scale.

RESULTS

The results confirm appreciable interfamilial heterogeneity as well as a high level of intrafamilial heterogeneity. Both ASD and combined ASD/BAP specific loci are apparent.

CONCLUSIONS

Inclusion of subclinical phenotypes such as BAP should be more widely employed in genetic studies of ASD as a way of identifying inherited genetic variants for the disorder. Moreover, the results underscore the need for approaches to identifying genetic risk factors in extended pedigrees that are robust to high levels of inter/intrafamilial locus and allelic heterogeneity.

Association of rare missense variants in the second intracellular loop of NaV1.7 sodium channels with familial autism

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder often accompanied by intellectual disability, language impairment and medical co-morbidities. The heritability of autism is high and multiple genes have been implicated as causal. However, most of these genes have been identified in de novo cases. To further the understanding of familial autism, we performed whole-exome sequencing on five families in which second- and third-degree relatives were affected. By focusing on novel and protein-altering variants, we identified a small set of candidate genes. Among these, a novel private missense C1143F variant in the second intracellular loop of the voltage-gated sodium channel Na_V1.7, encoded by the SCN9A gene, was identified in one family. Through electrophysiological analysis, we show that Na_V1.7^C1143F exhibits partial loss-of-function effects, resulting in slower recovery from inactivation and decreased excitability in cultured cortical neurons. Furthermore, for the same intracellular loop of Na_V1.7, we found an excess of rare variants in a case-control variant-burden study. Functional analysis of one of these variants, M932L/V991L, also demonstrated reduced firing in cortical neurons. However, although this variant is rare in Caucasians, it is frequent in Latino population, suggesting that genetic background can alter its effects on phenotype. Although the involvement of the SCN1A and SCN2A genes encoding Na_V1.1 and Na_V1.2 channels in de novo ASD has previously been demonstrated, our study indicates the involvement of inherited SCN9A variants and partial loss-of-function of Na_V1.7 channels in the etiology of rare familial ASD.

Assessing Rare Variation in Complex Traits

While genome-wide association studies have been very successful in identifying associations of common genetic variants with many different traits, the rarer frequency spectrum of the genome has not yet been comprehensively explored. Technological developments increasingly lift restrictions to access rare genetic variation. Dense reference panels enable improved genotype imputation for rarer variants in studies using DNA microarrays. Moreover, the decreasing cost of next generation sequencing makes whole exome and genome sequencing increasingly affordable for large samples. Large-scale efforts based on sequencing, such as ExAC, 100,000 Genomes, and TopMed, are likely to significantly advance this field.The main challenge in evaluating complex trait associations of rare variants is statistical power. The choice of population should be considered carefully because allele frequencies and linkage disequilibrium structure differ between populations. Genetically isolated populations can have favorable genomic characteristics for the study of rare variants.One strategy to increase power is to assess the combined effect of multiple rare variants within a region, known as aggregate testing. A  range of methods have been developed for this. Model performance depends on the genetic architecture of the region of interest.

Genome-wide association studies of albuminuria: towards genetic stratification in diabetes?

Genome-wide association studies (GWAS) have been very successful in unraveling the polygenic structure of several complex diseases and traits. In the case of albuminuria, despite the large sample size achieved by some studies, results look sparse with a limited number of loci reported so far. This review searched for GWAS studies of albumin excretion, albuminuria, and proteinuria. The resulting picture sets elements of uniqueness for albuminuria GWAS with respect to other complex traits. So far, very few loci associated with albuminuria have been validated by means of genome-wide significant evidence or formal replication. With rare exceptions, the validated loci are ethnicity specific. Within a given ethnicity, variants are common and have relatively large effects, especially in the presence of diabetes. In most cases, the identified variants were functional and a biological involvement of the target genes in renal damage was established. Recently reported variants associated with albuminuria in diabetes may be potentially combined into a genetic risk score, making it possible to rank diabetic patients by increasing risk of albuminuria. Validation of this model is required. To expand the understanding of the biological basis of albumin excretion regulation, future initiatives should achieve larger sample sizes and favor a transethnic study design.

f-treeGC: a questionnaire-based family tree-creation software for genetic counseling and genome cohort studies

BACKGROUND

The Tohoku Medical Megabank project aims to create a next-generation personalized healthcare system by conducting large-scale genome-cohort studies involving three generations of local residents in the areas affected by the Great East Japan Earthquake. We collected medical and genomic information for developing a biobank to be used for this healthcare system. We designed a questionnaire-based pedigree-creation software program named "f-treeGC," which enables even less experienced medical practitioners to accurately and rapidly collect family health history and create pedigree charts.

RESULTS

f-treeGC may be run on Adobe AIR. Pedigree charts are created in the following manner: 1) At system startup, the client is prompted to provide required information on the presence or absence of children; f-treeGC is capable of creating a pedigree up to three generations. 2) An interviewer fills out a multiple-choice questionnaire on genealogical information. 3) The information requested includes name, age, gender, general status, infertility status, pregnancy status, fetal status, and physical features or health conditions of individuals over three generations. In addition, information regarding the client and the proband, and birth order information, including multiple gestation, custody, multiple individuals, donor or surrogate, adoption, and consanguinity may be included. 4) f-treeGC shows only marriages between first cousins via the overlay function. 5) f-treeGC automatically creates a pedigree chart, and the chart-creation process is visible for inspection on the screen in real time. 6) The genealogical data may be saved as a file in the original format. The created/modified date and time may be changed as required, and the file may be password-protected and/or saved in read-only format. To enable sorting or searching from the database, the file name automatically contains the terms typed into the entry fields, including physical features or health conditions, by default. 7) Alternatively, family histories are collected using a completed foldable interview paper sheet named "f-sheet", which is identical to the questionnaire in f-treeGC.

CONCLUSIONS

We developed a questionnaire-based family tree-creation software, named f-treeGC, which is fully compliant with international recommendations for standardized human pedigree nomenclature. The present software simplifies the process of collecting family histories and pedigrees, and has a variety of uses, from genome cohort studies or primary care to genetic counseling.

Leveraging cell type specific regulatory regions to detect SNPs associated with tissue factor pathway inhibitor plasma levels

Tissue factor pathway inhibitor (TFPI) regulates the formation of intravascular blood clots, which manifest clinically as ischemic heart disease, ischemic stroke, and venous thromboembolism (VTE). TFPI plasma levels are heritable, but the genetics underlying TFPI plasma level variability are poorly understood. Herein we report the first genome-wide association scan (GWAS) of TFPI plasma levels, conducted in 251 individuals from five extended French-Canadian Families ascertained on VTE. To improve discovery, we also applied a hypothesis-driven (HD) GWAS approach that prioritized single nucleotide polymorphisms (SNPs) in (1) hemostasis pathway genes, and (2) vascular endothelial cell (EC) regulatory regions, which are among the highest expressers of TFPI. Our GWAS identified 131 SNPs with suggestive evidence of association (P-value < 5 × 10^-8 ), but no SNPs reached the genome-wide threshold for statistical significance. Hemostasis pathway genes were not enriched for TFPI plasma level associated SNPs (global hypothesis test P-value = 0.147), but EC regulatory regions contained more TFPI plasma level associated SNPs than expected by chance (global hypothesis test P-value = 0.046). We therefore stratified our genome-wide SNPs, prioritizing those in EC regulatory regions via stratified false discovery rate (sFDR) control, and reranked the SNPs by q-value. The minimum q-value was 0.27, and the top-ranked SNPs did not show association evidence in the MARTHA replication sample of 1,033 unrelated VTE cases. Although this study did not result in new loci for TFPI, our work lays out a strategy to utilize epigenomic data in prioritization schemes for future GWAS studies.

Whole exome association of rare deletions in multiplex oral cleft families

By sequencing the exomes of distantly related individuals in multiplex families, rare mutational and structural changes to coding DNA can be characterized and their relationship to disease risk can be assessed. Recently, several rare single nucleotide variants (SNVs) were associated with an increased risk of nonsyndromic oral cleft, highlighting the importance of rare sequence variants in oral clefts and illustrating the strength of family-based study designs. However, the extent to which rare deletions in coding regions of the genome occur and contribute to risk of nonsyndromic clefts is not well understood. To identify putative structural variants underlying risk, we developed a pipeline for rare hemizygous deletions in families from whole exome sequencing and statistical inference based on rare variant sharing. Among 56 multiplex families with 115 individuals, we identified 53 regions with one or more rare hemizygous deletions. We found 45 of the 53 regions contained rare deletions occurring in only one family member. Members of the same family shared a rare deletion in only eight regions. We also devised a scalable global test for enrichment of shared rare deletions.

Rare Variants in NOD1 Associated with Carotid Bifurcation Intima-Media Thickness in Dominican Republic Families

Cardiovascular disorders including ischemic stroke (IS) and myocardial infarction (MI) are heritable; however, few replicated loci have been identified. One strategy to identify loci influencing these complex disorders is to study subclinical phenotypes, such as carotid bifurcation intima-media thickness (bIMT). We have previously shown bIMT to be heritable and found evidence for linkage and association with common variants on chromosome 7p for bIMT. In this study, we aimed to characterize contributions of rare variants (RVs) in 7p to bIMT. To achieve this aim, we sequenced the 1 LOD unit down region on 7p in nine extended families from the Dominican Republic (DR) with strong evidence for linkage to bIMT. We then performed the family-based sequence kernel association test (famSKAT) on genes within the 7p region. Analyses were restricted to single nucleotide variants (SNVs) with population based minor allele frequency (MAF) <5%. We first analyzed all exonic RVs and then the subset of only non-synonymous RVs. There were 68 genes in our analyses. Nucleotide-binding oligomerization domain (NOD1) was the most significantly associated gene when analyzing exonic RVs (famSKAT p = 9.2x10^-4; number of SNVs = 14). We achieved suggestive replication of NOD1 in an independent sample of twelve extended families from the DR (p = 0.055). Our study provides suggestive statistical evidence for a role of rare variants in NOD1 in bIMT. Studies in mice have shown Nod1 to play a role in heart function and atherosclerosis, providing biologic plausibility for a role in bIMT thus making NOD1 an excellent bIMT candidate.

Genetic factors influencing risk to orofacial clefts: today's challenges and tomorrow's opportunities

Orofacial clefts include cleft lip (CL), cleft palate (CP), and cleft lip and palate (CLP), which combined represent the largest group of craniofacial malformations in humans with an overall prevalence of one per 1,000 live births. Each of these birth defects shows strong familial aggregation, suggesting a major genetic component to their etiology. Genetic studies of orofacial clefts extend back centuries, but it has proven difficult to define any single etiologic mechanism because many genes appear to influence risk. Both linkage and association studies have identified several genes influencing risk, but these differ across families and across populations. Genome-wide association studies have identified almost two dozen different genes achieving genome-wide significance, and there are broad classes of 'causal genes' for orofacial clefts: a few genes strongly associated with risk and possibly directly responsible for Mendelian syndromes which include orofacial clefts as a key phenotypic feature of the syndrome, and multiple genes with modest individual effects on risk but capable of disrupting normal craniofacial development under the right circumstances (which may include exposure to environmental risk factors). Genomic sequencing studies are now underway which will no doubt reveal additional genes/regions where variants (sequence and structural) can play a role in controlling risk to orofacial clefts. The real challenge to medicine and public health is twofold: to identify specific genes and other etiologic factors in families with affected members and then to devise effective interventions for these different biological mechanisms controlling risk to complex and heterogeneous birth defects such as orofacial clefts.

Cognitive, Linguistic, and Motor Abilities in a Multigenerational Family with Childhood Apraxia of Speech

Objective

This study describes the phenotype in a large family with a strong, multigenerational history of severe speech sound disorder (SSD) persisting into adolescence and adulthood in approximately half the cases. Aims were to determine whether a core phenotype, broader than speech, separated persistent from resolved SSD cases; and to ascertain the uniqueness of the phenotype relative to published cases.

Method

Eleven members of the PM family (9–55 years) were assessed across cognitive, language, literacy, speech, phonological processing, numeracy, and motor domains. Between group comparisons were made using the Mann–WhitneyU-test (p < 0.01). Participant performances were compared to normative data using standardized tests and to the limited published data on persistent SSD phenotypes.

Results

Significant group differences were evident on multiple speech, language, literacy, phonological processing, and verbal intellect measures without any overlapping scores. Persistent cases performed within the impaired range on multiple measures. Phonological memory impairment and subtle literacy weakness were present in resolved SSD cases.

Conclusion

A core phenotype distinguished persistent from resolved SSD cases that was characterized by a multiple verbal trait disorder, including Childhood Apraxia of Speech. Several phenotypic differences differentiated the persistent SSD phenotype in the PM family from the few previously reported studies of large families with SSD, including the absence of comorbid dysarthria and marked orofacial apraxia. This study highlights how comprehensive phenotyping can advance the behavioral study of disorders, in addition to forming a solid basis for future genetic and neural studies.

Identity-by-descent estimation with population- and pedigree-based imputation in admixed family data

Background

In the past few years, imputation approaches have been mainly used in population-based designs of genome-wide association studies, although both family- and population-based imputation methods have been proposed. With the recent surge of family-based designs, family-based imputation has become more important. Imputation methods for both designs are based on identity-by-descent (IBD) information. Apart from imputation, the use of IBD information is also common for several types of genetic analysis, including pedigree-based linkage analysis.

Methods

We compared the performance of several family- and population-based imputation methods in large pedigrees provided by Genetic Analysis Workshop 19 (GAW19). We also evaluated the performance of a new IBD mapping approach that we propose, which combines IBD information from known pedigrees with information from unrelated individuals.

Results

Different combinations of the imputation methods have varied imputation accuracies. Moreover, we showed gains from the use of both known pedigrees and unrelated individuals with our IBD mapping approach over the use of known pedigrees only.

Conclusions

Our results represent accuracies of different combinations of imputation methods that may be useful for data sets similar to the GAW19 pedigree data. Our IBD mapping approach, which uses both known pedigree and unrelated individuals, performed better than classical linkage analysis.

Genetic Complexity of Crohn's Disease in Two Large Ashkenazi Jewish Families

BACKGROUND & AIMS

Crohn's disease (CD) is a highly heritable disease that is particularly common in the Ashkenazi Jewish population. We studied 2 large Ashkenazi Jewish families with a high prevalence of CD in an attempt to identify novel genetic risk variants.

METHODS

Ashkenazi Jewish patients with CD and a positive family history were recruited from the University College London Hospital. We used genome-wide, single-nucleotide polymorphism data to assess the burden of common CD-associated risk variants and for linkage analysis. Exome sequencing was performed and rare variants that were predicted to be deleterious and were observed at a high frequency in cases were prioritized. We undertook within-family association analysis after imputation and assessed candidate variants for evidence of association with CD in an independent cohort of Ashkenazi Jewish individuals. We examined the effects of a variant in DUOX2 on hydrogen peroxide production in HEK293 cells.

RESULTS

We identified 2 families (1 with >800 members and 1 with >200 members) containing 54 and 26 cases of CD or colitis, respectively. Both families had a significant enrichment of previously described common CD-associated risk variants. No genome-wide significant linkage was observed. Exome sequencing identified candidate variants, including a missense mutation in DUOX2 that impaired its function and a frameshift mutation in CSF2RB that was associated with CD in an independent cohort of Ashkenazi Jewish individuals.

CONCLUSIONS

In a study of 2 large Ashkenazi Jewish with multiple cases of CD, we found the genetic basis of the disease to be complex, with a role for common and rare genetic variants. We identified a frameshift mutation in CSF2RB that was replicated in an independent cohort. These findings show the value of family studies and the importance of the innate immune system in the pathogenesis of CD.

PADRE: Pedigree-Aware Distant-Relationship Estimation

Accurate estimation of shared ancestry is an important component of many genetic studies; current prediction tools accurately estimate pairwise genetic relationships up to the ninth degree. Pedigree-aware distant-relationship estimation (PADRE) combines relationship likelihoods generated by estimation of recent shared ancestry (ERSA) with likelihoods from family networks reconstructed by pedigree reconstruction and identification of a maximum unrelated set (PRIMUS), improving the power to detect distant relationships between pedigrees. Using PADRE, we estimated relationships from simulated pedigrees and three extended pedigrees, correctly predicting 20% more fourth- through ninth-degree simulated relationships than when using ERSA alone. By leveraging pedigree information, PADRE can even identify genealogical relationships between individuals who are genetically unrelated. For example, although 95% of 13(th)-degree relatives are genetically unrelated, in simulations, PADRE correctly predicted 50% of 13(th)-degree relationships to within one degree of relatedness. The improvement in prediction accuracy was consistent between simulated and actual pedigrees. We also applied PADRE to the HapMap3 CEU samples and report new cryptic relationships and validation of previously described relationships between families. PADRE greatly expands the range of relationships that can be estimated by using genetic data in pedigrees.

FamPipe: An Automatic Analysis Pipeline for Analyzing Sequencing Data in Families for Disease Studies

In disease studies, family-based designs have become an attractive approach to analyzing next-generation sequencing (NGS) data for the identification of rare mutations enriched in families. Substantial research effort has been devoted to developing pipelines for automating sequence alignment, variant calling, and annotation. However, fewer pipelines have been designed specifically for disease studies. Most of the current analysis pipelines for family-based disease studies using NGS data focus on a specific function, such as identifying variants with Mendelian inheritance or identifying shared chromosomal regions among affected family members. Consequently, some other useful family-based analysis tools, such as imputation, linkage, and association tools, have yet to be integrated and automated. We developed FamPipe, a comprehensive analysis pipeline, which includes several family-specific analysis modules, including the identification of shared chromosomal regions among affected family members, prioritizing variants assuming a disease model, imputation of untyped variants, and linkage and association tests. We used simulation studies to compare properties of some modules implemented in FamPipe, and based on the results, we provided suggestions for the selection of modules to achieve an optimal analysis strategy. The pipeline is under the GNU GPL License and can be downloaded for free at http://fampipe.sourceforge.net.

A Comprehensive In Silico Analysis on the Structural and Functional Impact of SNPs in the Congenital Heart Defects Associated with NKX2-5 Gene-A Molecular Dynamic Simulation Approach

Congenital heart defects (CHD) presented as structural defects in the heart and blood vessels during birth contribute an important cause of childhood morbidity and mortality worldwide. Many Single nucletotide polymorphisms (SNPs) in different genes have been associated with various types of congenital heart defects. NKX 2–5 gene is one among them, which encodes a homeobox-containing transcription factor that plays a crucial role during the initial phases of heart formation and development. Mutations in this gene could cause different types of congenital heart defects, including Atrial septal defect (ASD), Atrial ventricular block (AVB), Tetralogy of fallot and ventricular septal defect. This highlights the importance of studying the impact of different SNPs found within this gene that might cause structural and functional modification of its encoded protein. In this study, we retrieved SNPs from the database (dbSNP), followed by identification of potentially deleterious Non-synonymous single nucleotide polymorphisms (nsSNPs) and prediction of their effect on proteins by computational screening using SIFT and Polyphen. Furthermore, we have carried out molecular dynamic simulation (MDS) in order to uncover the SNPs that would cause the most structural damage to the protein altering its biological function. The most important SNP that was found using our approach was rs137852685 R161P, which was predicted to cause the most damage to the structural features of the protein. Mapping nsSNPs in genes such as NKX 2–5 would provide valuable information about individuals carrying these polymorphisms, where such variations could be used as diagnostic markers.

Genome-Wide Studies of Type 2 Diabetes and Lipid Traits in Hispanics

Although disproportionately affected by increasing rates of type 2 diabetes and dyslipidemias, Hispanic populations are underrepresented in efforts to understand genetic susceptibility to these disorders. Where research has been undertaken, these populations have provided substantial insight into identification of novel risk-associated genes and have aided in the ability to fine map previously described risk loci. Genome-wide analyses in Hispanic and trans-ethnic populations have resulted in identification of more than 40 replicated or novel genes with significant effects for type 2 diabetes or lipid traits. Initial investigations into rare variant effects have identified new risk-associated variants private to Hispanic populations, and preliminary results suggest metagenomic approaches in Hispanic populations, such as characterizing the gut microbiome, will enable the development of new predictive tools and therapeutic targets for type 2 diabetes. Future genome-wide studies in expanded cohorts of Hispanics are likely to result in new insights into the genetic etiology of metabolic health.

SeqSIMLA2_exact: simulate multiple disease sites in large pedigrees with given disease status for diseases with low prevalence

It is difficult for current simulation tools to simulate sequence data in a pre-specified pedigree structure and pre-specified affection status. Previously, we developed a flexible tool, SeqSIMLA2, for simulating sequence data in either unrelated case-control or family samples with different disease and quantitative trait models. Here we extended the tool to efficiently simulate sequences with multiple disease sites in large pedigrees with a given disease status for each pedigree member, assuming that the disease prevalence is low.

AVAILABILITY AND IMPLEMENTATION

SeqSIMLA2_exact is implemented with C++ and is available at http://seqsimla.sourceforge.net.

Family-based approaches: design, imputation, analysis, and beyond

Participants in the family-based analysis group at Genetic Analysis Workshop 19 addressed diverse topics, all of which used the family data. Topics addressed included questions of study design and data quality control (QC), genotype imputation to augment available sequence data, and linkage and/or association analyses. Results show that pedigree-based tests that are sensitive to genotype error may be useful for QC. Imputation quality improved with inclusion of small amounts of pedigree information used to phase the data in evaluation of 5 commonly used approaches for imputation in samples of (typically) unrelated subjects. It improved still further when pedigree-based imputation using larger pedigrees was also added. An important distinction was made between methods that do versus do not make use of Mendelian transmission in pedigrees, because this serves as a key difference between underlying models and assumptions. Methods that model relatedness generally had higher power in association testing than did analyses that carry out testing in the presence of a transmission model, but this may reflect details of implementation and/or ability of more general methods to jointly include data from larger pedigrees. In either case, for single nucleotide polymorphism-set approaches, weights that incorporate information on functional effects may be more useful than those that are based only on allele frequencies. The overall results demonstrate that family data continue to provide important information in the search for trait loci.

Progress in methods for rare variant association

Empirical studies and evolutionary theory support a role for rare variants in the etiology of complex traits. Given this motivation and increasing affordability of whole-exome and whole-genome sequencing, methods for rare variant association have been an active area of research for the past decade. Here, we provide a survey of the current literature and developments from the Genetics Analysis Workshop 19 (GAW19) Collapsing Rare Variants working group. In particular, we present the generalized linear regression framework and associated score statistic for the 2 major types of methods: burden and variance components methods. We further show that by simply modifying weights within these frameworks we arrive at many of the popular existing methods, for example, the cohort allelic sums test and sequence kernel association test. Meta-analysis techniques are also described. Next, we describe the 6 contributions from the GAW19 Collapsing Rare Variants working group. These included development of new methods, such as a retrospective likelihood for family data, a method using genomic structure to compare cases and controls, a haplotype-based meta-analysis, and a permutation-based method for combining different statistical tests. In addition, one contribution compared a mega-analysis of family-based and population-based data to meta-analysis. Finally, the power of existing family-based methods for binary traits was compared. We conclude with suggestions for open research questions.

Family tree and ancestry inference: is there a need for a 'generational' consent?

Background

Genealogical research and ancestry testing are popular recreational activities but little is known about the impact of the use of these services on clients’ biological and social families. Ancestry databases are being enriched with self-reported data and data from deoxyribonucleic acid (DNA) analyses, but also are being linked to other direct-to-consumer genetic testing and research databases. As both family history data and DNA can provide information on more than just the individual, we asked whether companies, as a part of the consent process, were informing clients, and through them clients’ relatives, of the potential implications of the use and linkage of their personal data.

Methods

We used content analysis to analyse publically-available consent and informational materials provided to potential clients of ancestry and direct-to-consumer genetic testing companies to determine what consent is required, what risks associated with participation were highlighted, and whether the consent or notification of third parties was suggested or required.

Results

We identified four categories of companies providing: 1) services based only on self-reported data, such as personal or family history; 2) services based only on DNA provided by the client; 3) services using both; and 4) services using both that also have a research component. The amount of information provided on the potential issues varied significantly across the categories of companies. ‘Traditional’ ancestry companies showed the greatest awareness of the implications for family members, while companies only asking for DNA focused solely on the client. While in some cases companies included text recommending clients inform their relatives, showing they recognised the issues, often it was located within lengthy terms and conditions or privacy statements that may not be read by potential clients.

Conclusions

We recommend that companies should make it clearer that clients should inform third parties about their plans to participate, that third parties’ data will be provided to companies, and that that data will be linked to other databases, thus raising privacy and issues on use of data. We also suggest investigating whether a ‘generational consent’ should be created that would include more than just the individual in decisions about participating in genetic investigations.