Apolipoprotein E genotype is associated with macular pigment optical density.

PURPOSE: Age-related macular degeneration (AMD) is the most common cause of blindness in older people in developed countries, and risk factors for this condition may be classified as genetic and environmental. Apolipoprotein E is putatively involved in the transport of the macular pigment (MP) carotenoids lutein (L) and zeaxanthin (Z) in serum and may also influence retinal capture of these compounds. This study was designed to investigate the relationship between macular pigment optical density (MPOD) and ApoE genotype. METHODS: This was a cross-sectional study of 302 healthy adult subjects. Dietary intake of L and Z was assessed by food frequency questionnaire, and MPOD was measured by customized heterochromatic flicker photometry. Serum L and Z were measured by HPLC. ApoE genotyping was performed by direct polymerase chain reaction amplification and DNA nucleotide sequencing from peripheral blood. RESULTS: Genotype data were available on 300 of the 302 (99.3%) subjects. The mean (+/- SD) age of the subjects in this study was 47.89 +/- 11.05 (range, 21-66) years. Subjects were classed into one of three ApoE genotype groups, as follows: group 1, epsilon2epsilon2 or epsilon2epsilon3; group 2, epsilon3epsilon3; group 3, epsilon2epsilon4 or epsilon3epsilon4 or epsilon4epsilon4. All three groups were statistically comparable in terms of age, sex, body mass index, cigarette smoking, and dietary and serum levels of L and Z. There was a statistically significant association between ApoE genotype and MPOD. Subjects who had at least one epsilon4 allele had a higher MPOD across the macula than subjects without this allele (group 1 MPOD area, 0.70 +/- 0.40; group 2 MPOD area, 0.67 +/- 0.42; group 3 MPOD area, 0.85 +/- 0.46; one-way ANOVA, P = 0.014. CONCLUSIONS: These results suggest that ApoE genotype status is associated with MPOD. This association may explain, at least in part, the putative protective effect of the epsilon4 allele for AMD and is consistent with the view that apolipoprotein profile influences the transport and/or retinal capture of circulating L and/or Z.

Serotonin transporter genotype differentially modulates neural responses to emotional words following tryptophan depletion in patients recovered from depression and healthy volunteers

Previous studies have suggested that polymorphism in the serotonin transporter gene (5-HTTLPR) influences responses to serotonergic manipulation, with opposite effects in patients recovered from depression (rMDD) and controls. Here we sought to clarify the neurocognitive mechanisms underpinning these surprising results. Twenty controls and 23 rMDD subjects completed the study; functional magnetic resonance imaging (fMRI) and genotype data were available for 17 rMDD subjects and 16 controls. Following tryptophan or sham depletion, subjects performed an emotional-processing task during fMRI. Although no genotype effects on mood were identified, significant genotype(∗)diagnosis(∗)depletion interactions were observed in the hippocampus and subgenual cingulate in response to emotionally valenced words. In both regions, tryptophan depletion increased responses to negative words, relative to positive words, in high-expression controls, previously identified as being at low-risk for mood change following this procedure. By contrast, in higher-risk low-expression controls and high-expression rMDD subjects, tryptophan depletion had the opposite effect. Increased neural responses to negative words following tryptophan depletion may reflect an adaptive mechanism promoting resilience to mood change following perturbation of the serotonin system, which is reversed in sub-groups vulnerable to developing depressive symptoms. However, this interpretation is complicated by our failure to replicate previous findings of increased negative mood following tryptophan depletion.

Detection of nonrandom association of alleles from the distribution of the number of heterozygous loci in a sample.

The distribution of the number of heterozygous loci in two randomly chosen gametes or in a random diploid zygote provides information regarding the nonrandom association of alleles among different genetic loci. Two alternative statistics may be employed for detection of nonrandom association of genes of different loci when observations are made on these distributions: observed variance of the number of heterozygous loci (s2k) and a goodness-of-fit criterion (X2) to contrast the observed distribution with that expected under the hypothesis of random association of genes. It is shown, by simulation, that s2k is statistically more efficient than X2 to detect a given extent of nonrandom association. Asymptotic normality of s2k is justified, and X2 is shown to follow a chi-square (chi 2) distribution with partial loss of degrees of freedom arising because of estimation of parameters from the marginal gene frequency data. Whenever direct evaluations of linkage disequilibrium values are possible, tests based on maximum likelihood estimators of linkage disequilibria require a smaller sample size (number of zygotes or gametes) to detect a given level of nonrandom association in comparison with that required if such tests are conducted on the basis of s2k. Summarization of multilocus genotype (or haplotype) data, into the different number of heterozygous loci classes, thus, amounts to appreciable loss of information.

Genotypes of Bathymodiolus vent mussels from the Mid-Atlantic Ridge using SNP and mitochondrial markers

The provided file archive contains genotype data from mid-Atlantic hydrothermal vent mussels (genus Bathymodiolus) at 18 SNP loci and the mitochondrial ND4 gene (BMAR_Baz_Bpu_genotypes.txt). The subfolders denote statistical programs used in the multilocus genotyping study and contain input files and scripts that were used in the respective analyses.

Population genetic and dispersal modeling data for Bathymodiolus mussels from the Mid-Atlantic Ridge

The zip folder comprises a text file and a gzipped tar archive. 1) The text file contains individual genotype data for 90 SNPs, 9 microsatellites and the mitochondrial ND4 gene that were determined in deep-sea hydrothermal vent mussels from the Mid-Atlantic Ridge (genus Bathymodiolus). Mussel specimens are grouped according to the population (pop)/location from which they have been sampled (first column). The remaining columns contain the respective allele/haplotype codes for the different genetic loci (names in the header line). The data file is in CONVERT format and can be directly transformed into different input files for population genetic statistics. 2) The tar archive contains NetCDF files with larval dispersal probabilities for simulated annual larval releases between 1998 and 2007. For each simulated vent location (Menez Gwen, Lucky Strike, Rainbow, Vent 1-10) two NetCDF files are given, one for an assumed pelagic larval duration of 1 year and the other one for an assumed pelagic larval duration of 6 months (6m).

Minisatellite marker analysis of Trypanosoma brucei: Reconciliation of clonal, panmictic, and epidemic population genetic structures

The African trypanosome, Trypanosoma brucei, has been shown to undergo genetic exchange in the laboratory, but controversy exists as to the role of genetic exchange in natural populations. Much of the analysis to date has been derived from isoenzyme or randomly amplified polymorphic DNA data with parasite material from a range of hosts and geographical locations. These markers fail to distinguish between the human infective (T. b. rhodesiense) and nonhuman infective (T. b. brucei) “subspecies” so that parasites derived from hosts other than humans potentially contain both subspecies. To overcome some of the inherent problems with the use of such markers and diverse populations, we have analyzed a well-defined population from a discrete geographical location (Busoga, Uganda) using three recently described minisatellite markers. The parasites were primarily isolated from humans and cattle with the latter isolates further characterized by their ability to resist lysis by human serum (equivalent to human infectivity). The minisatellite markers show high levels of polymorphism, and from the data obtained we conclude that T. b. rhodesiense is genetically isolated from T. b. brucei and can be unambiguously identified by its multilocus genotype. Analysis of the genotype frequencies in the separated T. b. brucei and T. b. rhodesiense populations shows the former has an epidemic population structure whereas the latter is clonal. This finding suggests that the strong linkage disequilibrium observed in previous analyses, where human and nonhuman infective trypanosomes were not distinguished, results from the treatment of two genetically isolated populations as a single population.

Liver transplantation for HCV-associated liver cirrhosis: Predictors of outcomes in a population with significant genotype 3 and 4 distribution

End-stage liver disease associated with hepatitis C virus (HCV) infection is now the leading indication for liver transplantation in adults. However, reinfection of the graft is universal. We aimed to determine predictors of outcome of HCV-Iiver transplant recipients in the Australian and New Zealand communities. The following variables were analysed: demographic factors, coexistent pathology at the time of transplantation, HCV genotype, and donor age. Outcomes measures were: 1. mortality; 2. development of HCV-related complications, which were stage 3 or 4 fibrosis, or mortality from HCV-related graft failure, or both. Between January 1989 and December 30, 1999, 182 patients were transplanted for HCV-associated cirrhosis. The median follow-up period was 4 years (range, 0 to 13 years). Genotype data were available on 157 patients. The distribution of genotypes among the 157 patients was as follows: 36 (23%) genotype la, 30 (19%) genotype 1b, 4 (9%) genotype 1, 17 (11%) genotype 2, 41 (26%) genotype 3a, and 16 (10%) genotype 4. Eight (5%) patients were HCV-polymerase chain reaction (PCR)-negative (but HCV-antibody positive). Donor age and genotype 4 were associated with an increased risk of retransplantation or death (P < .001 and.05, respectively). Meanwhile, donor age, genotype 4, and pretransplant excess alcohol were risk factors for the development of HCV-related complications (P = .004, .008, and .02, respectively). In contrast, patients with genotype 3a were less likely to develop HCV-related complications (P = .05). In a population of HCV liver transplant recipients with a heterogeneous genotype distribution, donor age, and genotype 4, were predictors of a worse outcome, whereas genotype 3 was associated with a more favorable outcome.

New Advancements of Scalable Statistical Methods for Learning Latent Structures in Big Data

Constant technology advances have caused data explosion in recent years. Accord- ingly modern statistical and machine learning methods must be adapted to deal with complex and heterogeneous data types. This phenomenon is particularly true for an- alyzing biological data. For example DNA sequence data can be viewed as categorical variables with each nucleotide taking four different categories. The gene expression data, depending on the quantitative technology, could be continuous numbers or counts. With the advancement of high-throughput technology, the abundance of such data becomes unprecedentedly rich. Therefore efficient statistical approaches are crucial in this big data era.

Previous statistical methods for big data often aim to find low dimensional struc- tures in the observed data. For example in a factor analysis model a latent Gaussian distributed multivariate vector is assumed. With this assumption a factor model produces a low rank estimation of the covariance of the observed variables. Another example is the latent Dirichlet allocation model for documents. The mixture pro- portions of topics, represented by a Dirichlet distributed variable, is assumed. This dissertation proposes several novel extensions to the previous statistical methods that are developed to address challenges in big data. Those novel methods are applied in multiple real world applications including construction of condition specific gene co-expression networks, estimating shared topics among newsgroups, analysis of pro- moter sequences, analysis of political-economics risk data and estimating population structure from genotype data.

An X chromosome association scan of the Norfolk Island genetic isolate provides evidence for a novel migraine susceptibility locus at Xq12

Migraine is a common and debilitating neurovascular disorder with a complex envirogenomic aetiology. Numerous studies have demonstrated a preponderance of women affected with migraine and previous pedigree linkage studies in our laboratory have identified susceptibility loci on chromosome Xq24-Xq28. In this study we have used the genetic isolate of Norfolk Island to further analyse the X chromosome for migraine susceptibility loci. An association approach was employed to analyse 14,124 SNPs spanning the entire X chromosome. Genotype data from 288 individuals comprising a large core-pedigree, of which 76 were affected with migraine, were analysed. Although no SNP reached chromosome-wide significance (empirical α = 1×10−5) ranking by P-value revealed two primary clusters of SNPs in the top 25. A 10 SNP cluster represents a novel migraine susceptibility locus at Xq12 whilst a 11 SNP cluster represents a previously identified migraine susceptibility locus at Xq27. The strongest association at Xq12 was seen for rs599958 (OR = 1.75, P = 8.92×10−4), whilst at Xq27 the strongest association was for rs6525667 (OR = 1.53, P = 1.65×10−4). Further analysis of SNPs at these loci was performed in 5,122 migraineurs from the Women’s Genome Health Study and provided additional evidence for association at the novel Xq12 locus (P<0.05). Overall, this study provides evidence for a novel migraine susceptibility locus on Xq12. The strongest effect SNP (rs102834, joint P = 1.63×10−5) is located within the 5′UTR of the HEPH gene, which is involved in iron homeostasis in the brain and may represent a novel pathway for involvement in migraine pathogenesis.

Linkage mapping of CVD risk traits in the isolated Norfolk Island population

To understand the underlying genetic architecture of cardiovascular disease (CVD) risk traits, we undertook a genome-wide linkage scan to identify CVD quantitative trait loci (QTLs) in 377 individuals from the Norfolk Island population. The central aim of this research focused on the utilization of a genetically and geographically isolated population of individuals from Norfolk Island for the purposes of variance component linkage analysis to identify QTLs involved in CVD risk traits. Substantial evidence supports the involvement of traits such as systolic and diastolic blood pressures, high-density lipoprotein-cholesterol, low-density lipoprotein-cholesterol, body mass index and triglycerides as important risk factors for CVD pathogenesis. In addition to the environmental inXuences of poor diet, reduced physical activity, increasing age, cigarette smoking and alcohol consumption, many studies have illustrated a strong involvement of genetic components in the CVD phenotype through family and twin studies. We undertook a genome scan using 400 markers spaced approximately 10 cM in 600 individuals from Norfolk Island. Genotype data was analyzed using the variance components methods of SOLAR. Our results gave a peak LOD score of 2.01 localizing to chromosome 1p36 for systolic blood pressure and replicated previously implicated loci for other CVD relevant QTLs.

Genetic variants of angiotensin converting enzyme and methylenetetrahydrofolate reductase may act in combination to increase migraine susceptibility

Migraine, with and without aura (MA and MO), is a prevalent and complex neurovascular disorder that is likely to be influenced by multiple genes some of which may be capable of causing vascular changes leading to disease onset. This study was conducted to determine whether the ACE I/D gene variant is involved in migraine risk and whether this variant might act in combination with the previously implicated MTHFR C677T genetic variant in 270 migraine cases and 270 matched controls. Statistical analysis of the ACE I/D variant indicated no significant difference in allele or genotype frequencies (P > 0.05). However, grouping of genotypes showed a modest, yet significant, over-representation of the DD/ID genotype in the migraine group (88%) compared to controls (81%) (OR of 1.64, 95% CI: 1.00–2.69, P = 0.048). Multivariate analysis, including genotype data for the MTHFR C677T, provided evidence that the MTHFR (TT) and ACE (ID/DD) genotypes act in combination to increase migraine susceptibility (OR = 2.18, 95% CI: 1.15–4.16, P = 0.018). This effect was greatest for the MA subtype where the genotype combination corresponded to an OR of 2.89 (95% CI:1.47–5.72, P = 0.002). In Caucasians, the ACE D allele confers a weak independent risk to migraine susceptibility and also appears to act in combination with the C677T variant in the MTHFR gene to confer a stronger influence on the disease.

Closing the case of APOE in multiple sclerosis : no association with disease risk in over 29,000 subjects

Background Single nucleotide polymorphisms (SNPs) rs429358 (ε4) and rs7412 (ε2), both invoking changes in the amino-acid sequence of the apolipoprotein E (APOE) gene, have previously been tested for association with multiple sclerosis (MS) risk. However, none of these studies was sufficiently powered to detect modest effect sizes at acceptable type-I error rates. As both SNPs are only imperfectly captured on commonly used microarray genotyping platforms, their evaluation in the context of genome-wide association studies has been hindered until recently. Methods We genotyped 12 740 subjects hitherto not studied for their APOE status, imputed raw genotype data from 8739 subjects from five independent genome wide association studies datasets using the most recent high-resolution reference panels, and extracted genotype data for 8265 subjects from previous candidate gene assessments. Results Despite sufficient power to detect associations at genome-wide significance thresholds across a range of ORs, our analyses did not support a role of rs429358 or rs7412 on MS susceptibility. This included meta-analyses of the combined data across 13 913 MS cases and 15 831 controls (OR=0.95, p=0.259, and OR 1.07, p=0.0569, for rs429358 and rs7412, respectively). Conclusion Given the large sample size of our analyses, it is unlikely that the two APOE missense SNPs studied here exert any relevant effects on MS susceptibility.

SECA: SNP effect concordance analysis using genome-wide association summary results

The genomics era provides opportunities to assess the genetic overlap across phenotypes at the measured genotype level; however, current approaches require individual-level genome-wide association (GWA) single nucleotide polymorphism (SNP) genotype data in one or both of a pair of GWA samples. To facilitate the discovery of pleiotropic effects and examine genetic overlap across two phenotypes, I have developed a user-friendly web-based application called SECA to perform SNP effect concordance analysis using GWA summary results. The method is validated using publicly available summary data from the Psychiatric Genomics Consortium.

Extending genetic linkage analysis to diffusion tensor images to map single gene effects on brain fiber architecture

We extended genetic linkage analysis - an analysis widely used in quantitative genetics - to 3D images to analyze single gene effects on brain fiber architecture. We collected 4 Tesla diffusion tensor images (DTI) and genotype data from 258 healthy adult twins and their non-twin siblings. After high-dimensional fluid registration, at each voxel we estimated the genetic linkage between the single nucleotide polymorphism (SNP), Val66Met (dbSNP number rs6265), of the BDNF gene (brain-derived neurotrophic factor) with fractional anisotropy (FA) derived from each subject's DTI scan, by fitting structural equation models (SEM) from quantitative genetics. We also examined how image filtering affects the effect sizes for genetic linkage by examining how the overall significance of voxelwise effects varied with respect to full width at half maximum (FWHM) of the Gaussian smoothing applied to the FA images. Raw FA maps with no smoothing yielded the greatest sensitivity to detect gene effects, when corrected for multiple comparisons using the false discovery rate (FDR) procedure. The BDNF polymorphism significantly contributed to the variation in FA in the posterior cingulate gyrus, where it accounted for around 90-95% of the total variance in FA. Our study generated the first maps to visualize the effect of the BDNF gene on brain fiber integrity, suggesting that common genetic variants may strongly determine white matter integrity.

Polymorphisms in the receptor tyrosine kinase MERTK gene are associated with Multiple Sclerosis susceptibility

Multiple sclerosis (MS) is a debilitating, chronic demyelinating disease of the central nervous system affecting over 2 million people worldwide. The TAM family of receptor tyrosine kinases (TYRO3, AXL and MERTK) have been implicated as important players during demyelination in both animal models of MS and in the human disease. We therefore conducted an association study to identify single nucleotide polymorphisms (SNPs) within genes encoding the TAM receptors and their ligands associated with MS. Analysis of genotype data from a genome-wide association study which consisted of 1618 MS cases and 3413 healthy controls conducted by the Australia and New Zealand Multiple Sclerosis Genetics Consortium (ANZgene) revealed several SNPs within the MERTK gene (Chromosome 2q14.1, Accession Number NG_011607.1) that showed suggestive association with MS. We therefore interrogated 28 SNPs in MERTK in an independent replication cohort of 1140 MS cases and 1140 healthy controls. We found 12 SNPs that replicated, with 7 SNPs showing p-values of less than 10-5 when the discovery and replication cohorts were combined. All 12 replicated SNPs were in strong linkage disequilibrium with each other. In combination, these data suggest the MERTK gene is a novel risk gene for MS susceptibility. © 2011 Ma et al.