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The v-MFG test: investigating maternal, offspring and maternal-fetal genetic incompatibility effects on disease and viability.

The MFG test is a family-based association test that detects genetic effects contributing to disease in offspring, including offspring allelic effects, maternal allelic effects and MFG incompatibility effects. Like many other family-based association tests, it assumes that the offspring survival and the offspring-parent genotypes are conditionally independent provided the offspring is affected. However, when the putative disease-increasing locus can affect another competing phenotype, for example, offspring viability, the conditional independence assumption fails and these tests could lead to incorrect conclusions regarding the role of the gene in disease. We propose the v-MFG test to adjust for the genetic effects on one phenotype, e.g., viability, when testing the effects of that locus on another phenotype, e.g., disease. Using genotype data from nuclear families containing parents and at least one affected offspring, the v-MFG test models the distribution of family genotypes conditional on offspring phenotypes. It simultaneously estimates genetic effects on two phenotypes, viability and disease. Simulations show that the v-MFG test produces accurate genetic effect estimates on disease as well as on viability under several different scenarios. It generates accurate type-I error rates and provides adequate power with moderate sample sizes to detect genetic effects on disease risk when viability is reduced. We demonstrate the v-MFG test with HLA-DRB1 data from study participants with rheumatoid arthritis (RA) and their parents, we show that the v-MFG test successfully detects an MFG incompatibility effect on RA while simultaneously adjusting for a possible viability loss.

Alleles↗

Estimation and testing of genotype and haplotype effects in case-control studies: comparison of weighted regression and multiple imputation procedures.

A popular approach for testing and estimating genotype and haplotype effects associated with a disease outcome is to conduct a population-based case/control study, in which haplotypes are not directly observed but may be inferred probabilistically from unphased genotype data. A variety of methods exist to analyse the resulting data while accounting for the uncertainty in haplotype assignment, but most focus on the issue of testing the global null hypothesis that no genotype or haplotype effects exist. A more interesting question, once a region of disease association has been identified, is to estimate the relevant genotypic or haplotypic effects and to perform tests of complex null hypotheses such as the hypothesis that some loci, but not others, are associated with disease. Here I examine the assumptions behind, and the performance of, two classes of methods for addressing this question. The first is a weighted regression approach in which posterior probabilities of haplotype assignments are used as weights in a logistic regression analysis, generating a test based on either a weighted pseudo-likelihood, or a weighted log-likelihood. The second is a multiple imputation approach using either an improper procedure in which the posterior probabilities are used to generate replicate imputed data sets, or a proper data augmentation procedure. I compare these approaches to a simple expectation substitution (haplotype trend regression) approach. In simulations, all methods gave unbiased parameter estimation but the weighted pseudo-likelihood, expectation substitution and multiple imputation methods had superior confidence interval coverage. For the weighted pseudo-likelihood and expectation substitution methods it was necessary to estimate posterior haplotype assignment probabilities using the combined case/control data, whereas for the multiple imputation approaches it was necessary to estimate these probabilities in the case and control groups separately. Overall, multiple imputation was easiest approach to implement in standard statistical software and to extend to more complex models such as those that include gene-gene or gene-environment interactions.

Case-Control Studies↗

The Seattle Alzheimer's disease data set.

Forty families submitted to Genetic Analysis Workshop 8 are described. These are the families in the Seattle data set which have been typed for at least one genetic marker from the centromeric region of chromosome 21 or the q arm of chromosome 19. Thirteen of these families have average ages of onset below age 61 and are therefore considered to be early onset families. Seven of the families are of Volga German descent. Thirty-four of the families have autopsy documented Alzheimer's disease, including all 13 of the early onset pedigrees. The data set includes both the clinical and pedigree information available on the portions of the pedigrees used in the linkage analyses, genotype data on three loci on chromosome 19 and four loci on chromosome 21, and more extended family data on individuals who have not been included in the linkage analyses.

Adult↗

Effects of polymorphisms of methionine synthase and methionine synthase reductase on total plasma homocysteine in the NHLBI Family Heart Study.

The metabolism of homocysteine requires contributions of several enzymes and vitamin cofactors. Earlier studies identified a common polymorphism of methylenetetrahydrofolate reductase that was associated with mild hyperhomocysteinemia. Common variants of two other enzymes involved in homocysteine metabolism, methionine synthase and methionine synthase reductase, have also been identified. Methionine synthase catalyzes the remethylation of homocysteine to form methionine and methionine synthase reductase is required for the reductive activation of the cobalamin-dependent methionine synthase. The methionine synthase gene (MTR) mutation is an A to G substitution, 2756A-->G, which converts an aspartate to a glycine codon. The methionine synthase reductase gene (MTRR) mutation is an A to G substitution, 66A-->G, that converts an isoleucine to a methionine residue. To determine if these polymorphisms were associated with mild hyperhomocysteinemia, we investigated subjects from two of the NHLBI Family Heart Study field centers, Framingham and Utah. Total plasma homocysteine concentrations were determined after an overnight fast and after a 4-h methionine load test. MTR and MTRR genotype data were available for 677 and 562 subjects, respectively. The geometric mean fasting homocysteine was unrelated to the MTR or MTRR genotype categories (AA, AG, GG). After a methionine load, a weak positive association was observed between change in homocysteine after a methionine load and the number of mutant MTR alleles (P-trend=0.04), but this association was not statistically significant according to the overall F-statistic (P=0.12). There was no significant interaction between MTR and MTRR genotype or between these genotypes and any of the vitamins with respect to homocysteine concentrations. This study provides no evidence that these common MTR and MTRR mutations are associated with alterations in plasma homocysteine.

5-Methyltetrahydrofolate-Homocysteine S-Methyltran↗

Genetic identification by mass spectrometric analysis of single-nucleotide polymorphisms: ternary encoding of genotypes.

An approach to genetic identification using biallelic single-nucleotide polymorphism (SNP) genetic markers is described in which the three possible genotypes, AA, Aa, or aa, where "A" and "a" represent the two SNP alleles, are assigned a ternary (base 3) digit of 0, 1, or 2, respectively. Genotyping an individual over a panel of separate SNP markers produces a composite ternary genetic code that can be converted to an easily stored, decimal (base 10) genetic identification number. The unambiguous identification of 11 individuals is demonstrated using ternary genetic codes generated from MALDI-TOF mass spectrometric genotyping data from 7 different SNP markers.

Alleles↗

CLINICAL AND COGNITIVE PHENOTYPING OF COPY NUMBER VARIANTS ASSOCIATED WITH NEURODEVELOPMENTAL DISORDERS FROM A MULTI-ANCESTRY BIOBANK.

Clinical biobanks with electronic health records (EHRs) linked to genotype data continue to expand yielding an opportunity to further characterize disease-relevant genomic risk factors, yet few recall-by-genotype studies from biobanks have been published to date. For example, copy number variants (CNVs) that significantly increase risk for multiple neurodevelopmental disorders (NDDs) and negatively affect neurocognition, may present in up to 2% of population cohorts, with public health implications for ascertaining NDD CNV carriers. From BioMe, a multi-ancestry biobank derived from the Mount Sinai healthcare system (New York, NY), 892 adult participants were recontacted for deep phenotyping, including 335 NDD CNV carriers as well as comparators, 217 individuals with schizophrenia and 340 controls. Clinical and cognitive assessments were administered to each participant. There was no disclosure of genetic information. Eight percent of recontacted biobank participants completed the study (30 NDD CNV carriers across 15 unique loci, 20 schizophrenia and 23 controls). The study sample had a mean age of 48.8 (10.2) years, was 66% female and of diverse ancestry, 36% African, 34% Hispanic, and 26% European. Overall, 70% of 30 NDD-CNV carriers harbored at least one neuropsychiatric or developmental phenotype, including 40% with mood or anxiety disorders. Further, 22 NDD CNV carriers were significantly impaired compared to controls on digit span backwards (Beta=-1.76, FDR=0.04) and digit span sequencing (Beta=-2.01, FDR=0.04), but higher performing than schizophrenia on verbal learning (Beta=4.5, FDR=0.05). Thirty NDD CNV carriers were successfully recruited from a multi-ancestry biobank, as well as healthy controls and low-functioning individuals with schizophrenia. Deep phenotyping corroborated past reports, while also identifying discordance with EHRs. Future recall-by-genotype studies may further benchmark the study design and elucidate feasibility.

Biobank↗

Simultaneous genotyping, gene-expression measurement, and detection of allele-specific expression with oligonucleotide arrays.

Oligonucleotide microarrays provide a high-throughput method for exploring genomes. In addition to their utility for gene-expression analysis, oligonucleotide-expression arrays have also been used to perform genotyping on genomic DNA. Here, we show that in segregants from a cross between two unrelated strains of Saccharomyces cerevisiae, high-quality genotype data can also be obtained when mRNA is hybridized to an oligonucleotide-expression array. We were able to identify and genotype nearly 1000 polymorphisms at an error rate close to 3% in segregants and at an error rate of 7% in diploid strains, a performance comparable to methods using genomic DNA. In addition, we demonstrate how simultaneous genotyping and gene-expression profiling can reveal cis-regulatory variation by screening hundreds of genes for allele-specific expression. With this method, we discovered 70 ORFs with evidence for preferential expression of one allele in a diploid hybrid of two S. cerevisiae strains.

Alleles↗

Molecular typing of Mycobacterium bovis isolates from south-east Brazil by spoligotyping and RFLP.

The identification of 163 strains of Mycobacterium bovis by polymerase chain reaction (PCR) and microbiological tests was carried out on 252 tuberculous-like lesions (TLLs) collected from slaughtered cattle in south-east Brazil. This study compared the usefulness of three genotyping techniques, IS6110-restriction fragment length polymorphism (RFLP), polymorphic guanine-cytosine-rich sequence (PGRS)-RFLP and direct repeat (DR)-spoligotyping, as applied to M. bovis isolates. Based on IS6110-RFLP genotyping we selected a group of 23 isolates containing more than one IS6110 copy, along with 16 samples containing one IS6110 copy from different geographical areas, evenly distributed among dairy (eight) and beef cattle (eight). These selected isolates were analysed by PGRS-RFLP and DR-spoligotyping genotyping. Dairy cattle (17%) display a higher frequency of multiple IS6110 copies than beef cattle (10%). A comparison between the genotype data obtained fails to show a correlation between the main clusters found by the three techniques. However, the clustering of each genotyping procedure revealed that the majority of strains are closely related. The RFLP-PGRS patterns showed a sizable group (20.5%) containing a 5.5 kb fragment and the predominant spoligotype is similar to that from the BCG vaccine strain. Unexpectedly, four strains (2.4%) showed drug resistance to 0.2 microg/ml isoniazid and 20 microg/ml ethionamide, but none of them was resistant to rifampicin or other antibiotics tested.

Animals↗

[Study on hepatitis C virus genotyping in some parts of China].

OBJECTIVE: To study the genotypes of hepatitis C virus in some parts of China. METHODS: Twenty-seven sera of plasma donors from Guan county of Hebei province, Zhoukou district of Henan province, and 36 patients with chronic hepatitis C from Beijing and Qingdao cities were tested for HCV RNA by Amplicor PCR kit. Thirty-six of 38 HCV RNA positive sera were further genotyped, using INNO-LiP A HCV II kit. RESULTS: The HCV RNA positive rates of plasma donors and patients with chronic hepatitis C were 48.15% (13/27) and 69.44% (25/36) respectively. Genotyping data from 13 plasma donors and 23 patients with chronic hepatitis C showed that 29 (80.55%) were 1b, 5 (13.89%) were genotype 2, and 2 (5.56%) remained untyped. CONCLUSION: 1b seemed to be the prevalent HCV genotype in some parts of China.

Genotype↗

Conditional probability methods for haplotyping in pedigrees.

Efficient haplotyping in pedigrees is important for the fine mapping of quantitative trait locus (QTL) or complex disease genes. To reconstruct haplotypes efficiently for a large pedigree with a large number of linked loci, two algorithms based on conditional probabilities and likelihood computations are presented. The first algorithm (the conditional probability method) produces a single, approximately optimal haplotype configuration, with computing time increasing linearly in the number of linked loci and the pedigree size. The other algorithm (the conditional enumeration method) identifies a set of haplotype configurations with high probabilities conditional on the observed genotype data for a pedigree. Its computing time increases less than exponentially with the size of a subset of the set of person-loci with unordered genotypes and linearly with its complement. The size of the subset is controlled by a threshold parameter. The set of identified haplotype configurations can be used to estimate the identity-by-descent (IBD) matrix at a map position for a pedigree. The algorithms have been tested on published and simulated data sets. The new haplotyping methods are much faster and provide more information than several existing stochastic and rule-based methods. The accuracies of the new methods are equivalent to or better than those of these existing methods.

Animals↗

Mixture models of serum iron measures in population screening for hemochromatosis and iron overload.

Homozygosity for the C282Y mutation of the hemochromatosis gene on chromosome 6p (HFE) is a common genetic trait that increases susceptibility to iron overload. The authors describe and apply methodology developed for the analysis of phenotypic and genotypic data from 46,136 non-Hispanic Caucasians, a subset of the multi-ethnic cohort enrolled in the Hemochromatosis and Iron Overload Screening (HEIRS) Study. For analysis of the distribution of transferrin saturation (TS), mixtures of normal distributions were considered and the expectation-maximization (EM) algorithm was applied for parameter estimation. Maximized log-likelihoods were compared, and significance was assessed by resampling. Sensitivity, specificity, and predictive values from the modeled subpopulations were compared with the actual observed genotypes for C282Y and H63D mutations in the HFE gene. A strong association between HFE genotype and TS subpopulations was found in these data collected from different geographic regions, confirming the external validity of the statistical approach when applied to population-based data. It was concluded that mixture modeling of phenotypic data may provide a clinical guide for screening with gender-specific thresholds to identify potential samples for genetic testing.

Adult↗

The SNP Consortium website: past, present and future.

The SNP Consortium website (http://snp.cshl.org) has undergone many changes since its initial conception three years ago. The database back end has been changed from the venerable ACeDB to the more scalable MySQL engine. Users can access the data via gene or single nucleotide polymorphism (SNP) keyword searches and browse or dump SNP data to textfiles. A graphical genome browsing interface shows SNPs mapped onto the genome assembly in the context of externally available gene predictions and other features. SNP allele frequency and genotype data are available via FTP-download and on individual SNP report web pages. SNP linkage maps are available for download and for browsing in a comparative map viewer. All software components of the data coordinating center (DCC) website (http://snp.cshl.org) are open source.

Chromosome Mapping↗

Polymorphisms of interleukin (IL)-1alpha, IL-1beta, IL-6, IL-10, and IL-18 and the risk of ovarian cancer.

OBJECTIVE: Recent studies of ovarian cancer have suggested a role for inflammation in carcinogenesis. Data from a population-based case-control study in Hawaii were examined to assess the relation between polymorphisms in cytokines involved with the inflammatory response, specifically members of the interleukin (IL) family and the incidence of ovarian cancer. PATIENTS AND METHODS: The analysis of 182 epithelial ovarian cancer cases and 219 controls focused on the polymorphisms in the following genes: IL-1alpha, IL-1beta, IL-6, IL-10, and IL-18. Genotype data were obtained from blood samples collected in participants' homes, and reproductive, demographic, and lifestyle histories were collected during interview. RESULTS: There were no significant odds ratios (ORs) for ovarian cancer by allelic variants in any of the IL genes after adjusting for age, ethnicity, education, oral contraceptive pill use, pregnancy, and history of tubal ligation. Although there was a significantly reduced risk of ovarian cancer risk among women with an IL-1alpha (-4845) T allele compared to women with two G alleles (OR: 0.59; 95% confidence interval: 0.37-0.97) after adjustment for age and ethnicity, the trend was not significant (p = 0.10). Further examination of the data suggested that women with at least one IL-18 variant allele (a G to C transition at position -137) were at significantly decreased risk of advanced ovarian cancer (OR: 0.51; 95% confidence interval: 0.28-0.90) compared to women with the IL-18 GG genotype. There was a significant difference in the risk of ovarian cancer associated with the IL-18 C allele by stage at diagnosis (p = 0.04 for homogeneity in the ORs): cases with IL-18 GC or CC genotypes were less likely to be diagnosed at regional/distant stages. Analysis of the data within ethnic subgroups revealed a significant positive association of the heterozygous IL-18 GC genotype with ovarian cancer risk among Native Hawaiian women (OR: 9.96; 95% CI: 1.88-52.90). The OR for ovarian cancer was not significant for Native Hawaiian women homozygous for the IL-18 C allele, but only one case and control had the IL-18 CC genotype. CONCLUSIONS: Overall, this study does not support an association of selected IL-1alpha, IL-1beta, IL-6, IL-10, or IL-18 polymorphisms with the risk for ovarian cancer. However, the IL-18 G137C variant may be a marker for ovarian cancer progression or metastasis.

Adult↗

Maximum-likelihood estimation of haplotype frequencies in nuclear families.

The importance of haplotype analysis in the context of association fine mapping of disease genes has grown steadily over the last years. Since experimental methods to determine haplotypes on a large scale are not available, phase has to be inferred statistically. For individual genotype data, several reconstruction techniques and many implementations of the expectation-maximization (EM) algorithm for haplotype frequency estimation exist. Recent research work has shown that incorporating available genotype information of related individuals largely increases the precision of haplotype frequency estimates. We, therefore, implemented a highly flexible program written in C, called FAMHAP, which calculates maximum likelihood estimates (MLEs) of haplotype frequencies from general nuclear families with an arbitrary number of children via the EM-algorithm for up to 20 SNPs. For more loci, we have implemented a locus-iterative mode of the EM-algorithm, which gives reliable approximations of the MLEs for up to 63 SNP loci, or less when multi-allelic markers are incorporated into the analysis. Missing genotypes can be handled as well. The program is able to distinguish cases (haplotypes transmitted to the first affected child of a family) from pseudo-controls (non-transmitted haplotypes with respect to the child). We tested the performance of FAMHAP and the accuracy of the obtained haplotype frequencies on a variety of simulated data sets. The implementation proved to work well when many markers were considered and no significant differences between the estimates obtained with the usual EM-algorithm and those obtained in its locus-iterative mode were observed. We conclude from the simulations that the accuracy of haplotype frequency estimation and reconstruction in nuclear families is very reliable in general and robust against missing genotypes.

Algorithms↗

Profile of the BREATHE cohort for risk-based breast screening in Singapore.

The BREAst screening Tailored for HEr (BREATHE) study was established to pilot a personalised, risk-based breast cancer screening programme for a multi-ethnic Asian population. Between October 2021 and December 2023, 4592 women aged 35-59 were enrolled (73% response rate). Follow-up from February 2022 to June 2024 included 4112 participants (8.6% loss to follow-up). Data collected encompassed demographics, lifestyle factors, reproductive risks, breast cancer awareness, screening behaviours, programme satisfaction, mammography outcomes (density and recall status), and genotype data. Above-average breast cancer risk increased with age: 2% in women aged 35-39, 31% in 40-49, and 42% in 50-59. Findings suggests that women valued the knowledge of their breast cancer risk and were motivated to attend mammography. The BREATHE study confirms the feasibility and acceptability of a personalised risk-based screening programme in a multi-ethnic Asian population, highlighting the value of tailored protocols to improve early detection and outcomes. Further details are available in the study protocol and online at https://blog.nus.edu.sg/breathe/ .

Humans↗

Gaucher disease: gene frequencies and genotype/phenotype correlations.

Gaucher disease is the most prevalent lysosomal storage disease and has its highest incidence in the Ashkenazi Jewish population. Over 100 mutant alleles have been identified in affected patients, but four alleles, termed N370S, L444P, 84GG, and IVS2, have significant frequencies in this population. In affected patients, genotype data show that the presence of a single N370S allele is diagnostic of the type 1 or nonneuronopathic variant, whereas the L444P/L444P genotype is highly associated with neuronopathic variants in the Caucasian population. Large screening studies also indicate a significant underestimation (approximately two-fold) of the prevalence of the N370S/N370S genotype in the affected Ashkenazi Jewish patient population. These results indicate that the N370S/N370S genotype provides a necessary but not sufficient condition for the development of the Gaucher disease phenotype. The genotype/phenotype correlations and gene frequencies have significant impact on genetic counseling of at-risk couples and the future need for therapy of affected patients.

Alleles↗

PARL Leu262Val is not associated with fasting insulin levels in UK populations.

AIMS/HYPOTHESIS: PARL, the gene encoding presenilins-associated rhomboid-like protein, maps to chromosome 3q27 within a quantitative trait locus that influences components of the metabolic syndrome. Recently, an amino acid substitution (Leu262Val, rs3732581) in PARL was associated with fasting plasma insulin levels in a US white population (N=1031). This variant was also found to modify the positive association between age and fasting insulin. The aim of this study was to test whether these findings could be replicated in two UK population-based cohorts. METHODS: Participants from the Medical Research Council Ely and Hertfordshire cohort studies were genotyped for this variant using a SNaPshot primer extension assay and Taqman assay respectively. Full phenotypic and genotypic data were available for 3,666 study participants. RESULTS: Based on a dominant model, we found no association between the Leu262Val polymorphism and fasting insulin levels (p=0.79) or BMI (p=0.98). We did not observe the previously reported interaction between age and genotype on fasting insulin (p=0.14). CONCLUSIONS/INTERPRETATION: Despite having greater statistical power, our data do not support the previously reported association between PARL Leu262Val and fasting plasma insulin levels, a measure of insulin resistance. Our findings indicate that this variant is unlikely to be an important contributor to insulin resistance in UK populations.

Aged↗

A highly informative SNP linkage panel for human genetic studies.

We have developed a highly informative set of single-nucleotide polymorphism (SNP) assays designed for linkage mapping of the human genome. These assays were developed on a robust multiplexed assay system to provide a combination of very high accuracy and data completeness with high throughput for linkage studies. The linkage panel is comprised of approximately 4,700 SNPs with 0.39 average minor allele frequency and 624-kb average spacing. Based on almost 2 million genotypes, data quality was shown to be extremely high, with a 99.94% call rate, >99.99% reproducibility and 99.995% genotypes consistent with mendelian inheritance. We constructed a genetic map with an average 1.5-cM resolution using series of 28 CEPH pedigrees. The relative information content of this panel was higher than those of commonly used STR marker panels. The potent combination of this SNP linkage panel with the multiplexed assay system provides a previously unattainable level of performance for linkage studies.

Algorithms↗