Mapping genes with longitudinal phenotypes via Bayesian posterior probabilities

Most association studies focus on disease risk, with less attention paid to disease progression or severity. These phenotypes require longitudinal data. This paper presents a new method for analyzing longitudinal data to map genes in both population-based and family-based studies. Using simulated systolic blood pressure measurements obtained from Genetic Analysis Workshop 18, we cluster the phenotype data into trajectory subgroups. We then use the Bayesian posterior probability of being in the high subgroup as a quantitative trait in an association analysis with genotype data. This method maintains high power (\u3e80%) in locating genes known to affect the simulated phenotype for most specified significance levels (a). We believe that this method can be useful to aid in the discovery of genes that affect severity or progression of disease

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

Estimating relationships between phenotypes and subjects drawn from admixed families.

Background: Estimating relationships among subjects in a sample, within family structures or caused by population substructure, is complicated in admixed populations. Inaccurate allele frequencies can bias both kinship estimates and tests for association between subjects and a phenotype. We analyzed the simulated and real family data from Genetic Analysis Workshop 19, and were aware of the simulation model. Results: We found that kinship estimation is more accurate when marker data include common variants whose frequencies are less variable across populations. Estimates of heritability and association vary with age for longitudinally measured traits. Accounting for local ancestry identified different true associations than those identified by a traditional approach. Principal components aid kinship estimation and tests for association, but their utility is influenced by the frequency of the markers used to generate them. Conclusions: Admixed families can provide a powerful resource for detecting disease loci, as well as analytical challenges. Allele frequencies, although difficult to adequately estimate in admixed populations, have a strong impact on the estimation of kinship, ancestry, and association with phenotypes. Approaches that acknowledge population structure in admixed families outperform those which ignore it

Genetic Candidate Variants in Two Multigenerational Families with Childhood Apraxia of Speech

Childhood apraxia of speech (CAS) is a severe and socially debilitating form of speech sound disorder with suspected genetic involvement, but the genetic etiology is not yet well understood. Very few known or putative causal genes have been identified to date, e.g., FOXP2 and BCL11A. Building a knowledge base of the genetic etiology of CAS will make it possible to identify infants at genetic risk and motivate the development of effective very early intervention programs. We investigated the genetic etiology of CAS in two large multigenerational families with familial CAS. Complementary genomic methods included Markov chain Monte Carlo linkage analysis, copy-number analysis, identity-by-descent sharing, and exome sequencing with variant filtering. No overlaps in regions with positive evidence of linkage between the two families were found. In one family, linkage analysis detected two chromosomal regions of interest, 5p15.1-p14.1, and 17p13.1-q11.1, inherited separately from the two founders. Single-point linkage analysis of selected variants identified CDH18 as a primary gene of interest and additionally, MYO10, NIPBL, GLP2R, NCOR1, FLCN, SMCR8, NEK8, and ANKRD12, possibly with additive effects. Linkage analysis in the second family detected five regions with LOD scores approaching the highest values possible in the family. A gene of interest was C4orf21(ZGRF1) on 4q25-q28.2. Evidence for previously described causal copy-number variations and validated or suspected genes was not found. Results are consistent with a heterogeneous CAS etiology, as is expected in many neurogenic disorders. Future studies will investigate genome variants in these and other families with CAS

Multipoint genome-wide linkage scan for nonword repetition in a multigenerational family further supports chromosome 13q as a locus for verbal trait disorders

Verbal trait disorders encompass a wide range of conditions and are marked by deficits in five domains that impair a person’s ability to communicate: speech, language, reading, spelling, and writing. Nonword repetition is a robust endophenotype for verbal trait disorders that is sensitive to cognitive processes critical to verbal development, including auditory processing, phonological working memory, and motor planning and programming. In the present study, we present a six-generation extended pedigree with a history of verbal trait disorders. Using genome-wide multipoint variance component linkage analysis of nonword repetition, we identified a region spanning chromosome 13q14–q21 with LOD = 4.45 between 52 and 55 cM, spanning approximately 5.5 Mb on chromosome 13. This region overlaps with SLI3, a locus implicated in reading disability in families with a history of specific language impairment. Our study of a large multigenerational family with verbal trait disorders further implicates the SLI3 region in verbal trait disorders. Future studies will further refine the specific causal genetic factors in this locus on chromosome 13q that contribute to language traits

Nuclear energy in the post-genomic era

\u27Genomics,\u27 the term first proposed in 1986, is the discipline of understanding genomes powered by an unprecedented accumulation of information on genetic sequences of a wide archive of life forms, foremost of which is the genome of man. After more than two decades of international effort in decoding life\u27s alphabet and culminating with the first working draft of the human DNA this year, the \u27postgenomic\u27 era aims to annotate the existing genetic data, elucidate gene functions and find revolutionary applications in almost all branches of life and physical sciences, leaving no bough untouched, not even nuclear science

Radioactive PTT as part of screening protocol for prospecting radiation workers

Heterozygous mutations in BRCA1 or BRCA2 (breast cancer)have been found to be associated with enhanced cellular radio sensitivity with impaired proliferative capacity after irradiation and could predispose increased risk of radiation-induced mutagenesis and carcinogenesis (1,2). Deficient repair mechanism exhibited by lymphocytes from breast cancer patients provides associated vulnerability to genotoxicity of ionizing radiation. Other genes as also play a role in terms o clinical radiation hypersensitivity needed in predicting response to radiotherapy. However, relaxation of cell cycle checkpoints, production of micronuclei, and loss of proliferative capacity which have been exhibited by impairment of irradiated cells lacking functional BRCA1 and BRCA2, accentuate the notion that heterozygous women may respond differently to radiation. The radioactive protein truncation test (PTT), utilized as screening procedures to detect frameshift mutations, can be employed to clarify radio sensitivity of individuals carrying a mutated BRCA1 gene. It can therefore, be incorporated in the series of clinical assays used in standard screening protocols for prospective nuclear facility workers

Divergent Haplotypes and Human History as Revealed in a Worldwide Survey of X-Linked DNA Sequence Variation

Thepopulation genetic historyof a10.1-kbp noncodingregion ofthe humanXchromosome was studiedusing the malesof the HGDP-CEPH Human Genome Diversity Panel (672 individuals from 52 populations). The geographic distribution of patterns of variation was roughly consistent with previous studies, with the major exception that 1 highly divergent haplotype(haplotypeX,hX)wasobservedatlowfrequencyinwidelyscattered non-Africanpopulationsandnotatallobserved in sub-Saharan African populations. Microsatellite (short tandem repeat) variation within the sequenced region was low among copies of hX, even though the estimated time of ancestry of hX and other sequences was 1.44 Myr. The estimated age of the common ancestor of all hX copies was 5,230 years (95% consistency index: 2,000–75,480 years). To further address the presence of hX in Africa, additional samples from Chad and Tanzania were screened. Five additional copies of hX were observed, consistent with a history in which hX was present in Africa prior to the migration of modern humans out of Africa and with eastern Africa being the source of non-African modern human populations. Taken together, these features of hX—that it is much older than other haplotypes and uncommon and patchily distributed throughout Africa, Europe, and Asia—present a cautionary tale for interpretations of human history

PBAP: a pipeline for file processing and quality control of pedigree data with dense genetic markers

Motivation: Huge genetic datasets with dense marker panels are now common. With the availability of sequence data and recognition of importance of rare variants, smaller studies based on pedigrees are again also common. Pedigree-based samples often start with a dense marker panel, a subset of which may be used for linkage analysis to reduce computational burden and to limit linkage disequilibrium between single-nucleotide polymorphisms (SNPs). Programs attempting to select markers for linkage panels exist but lack flexibility. Results: We developed a pedigree-based analysis pipeline (PBAP) suite of programs geared towards SNPs and sequence data. PBAP performs quality control, marker selection and file preparation. PBAP sets up files for MORGAN, which can handle analyses for small and large pedigrees, typically human, and results can be used with other programs and for downstream analyses. We evaluate and illustrate its features with two real datasets

Single-Variant and Multi-Variant Trend Tests for Genetic Association with Next-Generation Sequencing That Are Robust to Sequencing Error. Human Heredity

As with any new technology, next generation sequencing (NGS) has potential advantages and potential challenges. One advantage is the identification of multiple causal variants for disease that might otherwise be missed by SNP-chip technology. One potential challenge is misclassification error (as with any emerging technology) and the issue of power loss due to multiple testing. Here, we develop an extension of the linear trend test for association that incorporates differential misclassification error and may be applied to any number of SNPs. We call the statistic the linear trend test allowing for error, applied to NGS, or LTTae,NGS. This statistic allows for differential misclassification. The observed data are phenotypes for unrelated cases and controls, coverage, and the number of putative causal variants for every individual at all SNPs. We simulate data considering multiple factors (disease mode of inheritance, genotype relative risk, causal variant frequency, sequence error rate in cases, sequence error rate in controls, number of loci, and others) and evaluate type I error rate and power for each vector of factor settings. We compare our results with two recently published NGS statistics. Also, we create a fictitious disease model, based on downloaded 1000 Genomes data for 5 SNPs and 388 individuals, and apply our statistic to that data. We find that the LTTae,NGS maintains the correct type I error rate in all simulations (differential and non-differential error), while the other statistics show large inflation in type I error for lower coverage. Power for all three methods is approximately the same for all three statistics in the presence of non-differential error. Application of our statistic to the 1000 Genomes data suggests that, for the data downloaded, there is a 1.5% sequence misclassification rate over all SNPs. Finally, application of the multi-variant form of LTTae,NGS shows high power for a number of simulation settings, although it can have lower power than the corresponding single variant simulation results, most probably due to our specification of multi-variant SNP correlation values. In conclusion, our LTTae,NGS addresses two key challenges with NGS disease studies; first, it allows for differential misclassification when computing the statistic; and second, it addresses the multiple-testing issue in that there is a multi-variant form of the statistic that has only one degree of freedom, and provides a single p-value, no matter how many loci