Biomedical subjects
Publications and source records attributed to Michael Knapp.
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BACKGROUND: A dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis has been proposed as an important pathogenic factor in depression. Genetic variants of FKBP5, a protein of the HPA system modulating the glucocorticoid receptor, have been reported to be genetically associated with improved response to medical treatment and an increase of depressive episodes. METHODS: We examined three single nucleotide polymorphisms (SNPs) in FKBP5, rs4713916 in the proposed promoter region, rs1360780 in the second intron and rs3800373 in the 3'-untranslated region (3'-UTR), in a case-control study of Caucasian origin (affective psychosis: n = 248; controls: n = 188) for genetic association and association with disease related traits. RESULTS: Allele and genotype frequencies of rs4713916, rs1360780 and rs3800373 were not significantly different between cases and controls. Two three-locus haplotypes, G-C-T and A-T-G, accounted for 86.2% in controls. Odds ratios were not increased between cases and controls, except the rare haplotype G-C-G (OR 6.81), representing 2.1% of cases and 0.3% of controls. The frequency of rs4713916AG in patients deviated from expected Hardy-Weinberg equilibrium, the genotype AA at rs4713916 in monopolar depression (P = 0.011), and the two-locus haplotype rs1360780T--rs3800373T in the total sample (overall P = 0.045) were nominally associated with longer continuance of disease. CONCLUSION: Our data do not support a significant genetic contribution of FKBP5 polymorphisms and haplotypes to affective psychosis, and the findings are inconclusive regarding their contribution to disease-related traits.
Despite the potential pitfalls of stratification, population-based association studies nowadays are being conducted more often than family-based association studies. However, the mechanism of genomic imprinting has lately been implicated in the etiology of genetic complex diseases and can be detected using statistics only in family-based designs. Powerful tests for association and imprinting have been proposed previously for case-parent trios and single markers. Since the power of association studies can be improved if multiple affected children and haplotypes are considered, we extended the parental asymmetry test (PAT) for imprinting to a test that is suited for both general nuclear families and haplotypes, called HAP-PAT. Significance of the HAP-PAT is determined via a Monte-Carlo simulation procedure. In addition to the HAP-PAT, we modified a haplotype-based association test, proposed by us before, in such a way that either only paternal or maternal transmissions contribute to the test statistic. The approaches were implemented in FAMHAP and we evaluated their performance under a variety of disease models. We were able to demonstrate the usefulness of our haplotype-based approaches to detect parent-of-origin effects. Furthermore, we showed that also in the presence of imprinting it is more reasonable to consider all affected children of a nuclear family, than to randomly select one affected child from each family and to conduct a trio study using the selected individuals.
The dopamine hypothesis of schizophrenia proposes an inherited or acquired presynaptic hyperactivity of dopaminergic neurons. The human dopamine transporter gene (hSLC6A3; hDAT) represents one major mechanism for the termination of dopaminergic neurotransmission. This study examines the degree of genetic association of the 5'-untranslated region (5'-UTR) of the hSLC6A3 to schizophrenia in a family-based association design. Five single nucleotide polymorphisms (SNPs) derived by a previous systematic mutation scan approximately 1.2 kb of the 5'-UTR of the hSLC6A3 locus were genotyped for transmission disequilibrium between 82 index cases (56 males) with schizophrenia and their biological parents. We observed no preferential transmission of alleles from heterozygous parents to affected offspring. Five estimated haplotypes accounted for a frequency of 90% in the index cases, and were identical in cases and non-transmitted parental control haplotypes. Distinct five-locus-genotypes accumulated in schizophrenia compared to parental controls at P-value 0.0038 with odds-ratio of 2.02 (95% CI 0.99-4.14). In conclusion, our present findings support the genetic involvement of distinct hSLC6A3 genotypes in schizophrenia. We propose replication in extended samples and examination of the functional relevance of the associated genotypes on human dopamine transporter expression.
Previously applied test statistics for affected sib pairs (ASP) have been criticized for not fully exploiting the power of a given sample, because they do not account for incomplete informativity of an affected sib pair. To circumvent this problem, recently a new test had been proposed which weighs families proportional to their marker informativity. Here, the behavior of this new test is explored under scenarios considered to be relevant in the context of complex diseases. The results show that the new test does not represent an improvement. The asymptotic version of the new test tends to be markedly anticonservative even for larger sample sizes, whereas the permutation procedure proposed for the simulation of exact P values is at least questionable. Most importantly, the new test is less powerful than its competitors, especially in case of low marker informativity it was designed for.
Undetected genotyping errors pose a problem in genetic epidemiological studies, as they may invalidate statistical analysis or reduce its power. Haplotype analysis requires an improved standard of the data, because a haplotype can be inferred correctly only if the genotypes of all its markers are correct. Here, we present a method that identifies probable genotyping errors in trio samples with the help of the estimated haplotype frequency distribution of the sample. If the likelihood of the most likely haplotype explanation depends strongly on just one genotype, in the sense that setting the genotype to be missing leads to a much more likely haplotype explanation, this genotype is considered as a potential genotyping error. We describe a method that systematically searches the whole data set for such potential errors. Based on the haplotype distribution of a real data set, we carry out a simulation study to estimate the sensitivity and specificity of the method. In addition, we apply our approach to the real data set itself. Potentially erroneous genotypes are re-determined via sequencing. The results of both the simulation study and of the application to the real data set show that a considerable proportion of true genotyping errors is detected and that the number of false-positive signals is acceptable. We conclude that it is indeed possible to identify probable genotyping errors by considering haplotypes. The method described here will be part of the next release of our FAMHAP software.
OBJECTIVES: To determine the degree of association of five single nucleotide polymorphisms at the 5'-untranslated region (5'-UTR) of the human dopamine transporter gene (hSLC6A3; hDAT1) in bipolar affective disorder. METHODS: In a case-control design study, the polymorphisms were genotyped for allelic and genotypic distribution between 105 index cases (50 males) with bipolar affective disorder according to DSM IV and 199 unaffected control subjects (120 males). RESULTS: At the 5'-UTR locus of hSLC6A3, no significant allelic or genotypic differences were observed between index cases and controls. However, distinct 5-locus genotypes accumulated in subjects with bipolar affective disorder compared to control subjects (p = 0.029, odds ratio 1.84, 95% confidence interval 1.12-3.02). CONCLUSIONS: In conclusion, our data do not provide evidence for a major role of the 5'-UTR of the dopamine transporter gene in bipolar affective disorder. A minor contribution of distinct genotypes may be possible and warrants replication in extended samples.
BACKGROUND: The chromosome 22q11 region is proposed as a major candidate locus for susceptibility genes to schizophrenia. Recently, the gene ZDHHC8 encoding a putative palmitoyltransferase at 22q11 was proposed to increase liability to schizophrenia based on both animal models and human association studies by significant over-transmission of allele rs175174A in female, but not male subjects with schizophrenia. METHODS: Given the genetic complexity of schizophrenia and the potential genetic heterogeneity in different populations, we examined rs175174 in 204 German proband-parent triads and in an independent case-control study (schizophrenic cases: n = 433; controls: n = 186). RESULTS: In the triads heterozygous parents transmitted allele G preferentially to females, and allele A to males (heterogeneity chi2 = 4.43; p = 0.035). The case-control sample provided no further evidence for overall or gender-specific effects regarding allele and genotype frequency distributions. CONCLUSION: The findings on rs175174 at ZDHHC8 are still far from being conclusive, but evidence for sexual dimorphism is moderate, and our data do not support a significant genetic contribution of rs175174 to the aetiopathogenesis of schizophrenia.
A rapid and sensitive method for the simultaneous quantification of alpha-tocopherol, beta-carotene, beta-cryptoxanthin, lutein and zeaxanthin in botanical materials has been developed using normal phase liquid chromatography-atmospheric pressure chemical ionization-tandem mass spectrometry (NP-LC-APCI-MS/MS). A systematic extraction procedure for different botanical materials was described and the extraction solvents were matched with normal-phase LC requirement. Quantification was performed by using the external standards and standard calibration curves were linear between 35 and 8505 ng/mL for alpha-tocopherol, 64-15,552 ng/mL for beta-carotene, 40-9720 ng/mL for beta-cryptoxanthin, 70-17,010 ng/mL for lutein and 64-15,552 ng/mL for zeaxanthin with regression coefficient r2 > 0.9996. The limits of quantification (LOQ) were 35, 64, 40, 70 and 66 ng/mL for alpha-tocopherol, beta-carotene, beta-cryptoxanthin, lutein and zeaxanthin, respectively.
In the context of haplotype association analysis of unphased genotype data, methods based on Monte-Carlo simulations are often used to compensate for missing or inappropriate asymptotic theory. Moreover, such methods are an indispensable means to deal with multiple testing problems. We want to call attention to a potential trap in this usually useful approach: The simulation approach may lead to strongly inflated type I errors in the presence of different missing rates between cases and controls, depending on the chosen test statistic. Here, we consider four different testing strategies for haplotype analysis of case-control data. We recommend to interpret results for data sets with non-comparable distributions of missing genotypes with special caution, in case the test statistic is based on inferred haplotypes per individual. Moreover, our results are important for the conduction and interpretation of genome-wide association studies.
Previously, it has been shown for affected sib pairs that the mean test is the uniformly (in theta) most powerful test in case of a multiplicative mode of inheritance and that the mean test is equivalent to parametric linkage analysis calculated under an assumed multiplicative mode of inheritance. Here, these two results are extended to samples consisting of affected sib triplets. For affected sib quadruplets, however, it is shown that these results are no longer valid.
Nothofagus (southern beech), with an 80-million-year-old fossil record, has become iconic as a plant genus whose ancient Gondwanan relationships reach back into the Cretaceous era. Closely associated with Wegener's theory of "Kontinentaldrift", Nothofagus has been regarded as the "key genus in plant biogeography". This paradigm has the New Zealand species as passengers on a Moa's Ark that rafted away from other landmasses following the breakup of Gondwana. An alternative explanation for the current transoceanic distribution of species seems almost inconceivable given that Nothofagus seeds are generally thought to be poorly suited for dispersal across large distances or oceans. Here we test the Moa's Ark hypothesis using relaxed molecular clock methods in the analysis of a 7.2-kb fragment of the chloroplast genome. Our analyses provide the first unequivocal molecular clock evidence that, whilst some Nothofagus transoceanic distributions are consistent with vicariance, trans-Tasman Sea distributions can only be explained by long-distance dispersal. Thus, our analyses support the interpretation of an absence of Lophozonia and Fuscospora pollen types in the New Zealand Cretaceous fossil record as evidence for Tertiary dispersals of Nothofagus to New Zealand. Our findings contradict those from recent cladistic analyses of biogeographic data that have concluded transoceanic Nothofagus distributions can only be explained by vicariance events and subsequent extinction. They indicate that the biogeographic history of Nothofagus is more complex than envisaged under opposing polarised views expressed in the ongoing controversy over the relevance of dispersal and vicariance for explaining plant biodiversity. They provide motivation and justification for developing more complex hypotheses that seek to explain the origins of Southern Hemisphere biota.
Genetically complex diseases are caused by interacting environmental factors and genes. As a consequence, statistical methods that consider multiple unlinked genomic regions simultaneously are desirable. Such consideration, however, may lead to a vast number of different high-dimensional tests whose appropriate analysis pose a problem. Here, we present a method to analyze case-control studies with multiple SNP data without phase information that considers gene-gene interaction effects while correcting appropriately for multiple testing. In particular, we allow for interactions of haplotypes that belong to different unlinked regions, as haplotype analysis often proves to be more powerful than single marker analysis. In addition, we consider different marker combinations at each unlinked region. The multiple testing issue is settled via the minP approach; the P value of the "best" marker/region configuration is corrected via Monte-Carlo simulations. Thus, we do not explicitly test for a specific pre-defined interaction model, but test for the global hypothesis that none of the considered haplotype interactions shows association with the disease. We carry out a simulation study for case-control data that confirms the validity of our approach. When simulating two-locus disease models, our test proves to be more powerful than association methods that analyze each linked region separately. In addition, when one of the tested regions is not involved in the etiology of the disease, only a small amount of power is lost with interaction analysis as compared to analysis without interaction. We successfully applied our method to a real case-control data set with markers from two genes controlling a common pathway. While classical analysis failed to reach significance, we obtained a significant result even after correction for multiple testing with our proposed haplotype interaction analysis. The method described here has been implemented in FAMHAP.
The brain synaptic vesicular amine transporter SLCA18A2 is a key component for the uptake of monoamines like dopamine or serotonin into vesicles. We have analyzed seven DNA polymorphisms located in the genomic region of SLC18A2 for association with alcohol- and nicotine dependence, using a family-based design. Our sample comprised 131 families with alcohol-dependent offspring and 96 families with at least one nicotine-dependent offspring. For the alcohol-dependent sample, we found statistical significant association for two single markers (rs363387, P=0.03; rs363333, P=0.0066) as well as for several haplotypes (minimal P=0.0038). When the sample with alcohol dependence was stratified according to gender, we observed increased association for the male subgroup (rs363387, P=0.0011). None of the markers showed association in the sample of families with nicotine dependence. However, analysis of a combined sample of alcohol and nicotine-dependent families resulted in single markers as well as several haplotypes showing statistical significant association with substance dependence (minimal P=0.0044). We conclude that DNA polymorphisms located in SLC18A2 might contribute to the development of substance dependence.
This paper proposes family based Hotelling's T(2) tests for high resolution linkage disequilibrium (LD) mapping or association studies of complex diseases. Assume that genotype data of multiple markers or haplotype blocks are available for a sample of nuclear families, in which some offspring are affected. Paired Hotelling's T(2) test statistics are proposed for a high resolution association study using parents as controls for affected offspring, based on two coding methods: haplotype/allele coding and genotype coding. The paired Hotelling's T(2) tests take not only the correlation between the haplotype blocks or markers into account, but also take the correlation within each parent-offspring pair into account. The method extends two sample Hotelling's T(2) test statistics for population case control association studies, which are not valid for family data due to correlation of genetic data among family members. The validity of the proposed method is justified by rigorous mathematical and statistical proof under the large sample theory. The non-centrality parameter approximations of the test statistics are calculated for power and sample size calculations. From power comparison and type I error calculations, it is shown that the test statistic based on haplotype/allele coding is advantageous over the test statistic of genotype coding. Analysis using multiple markers may provide higher power than single marker analysis. If only one marker is utilized the power of the test statistic based on haplotype/allele coding is nearly identical to that of 1-TDT. Moreover, a permutation procedure is provided for data analysis. The method is applied to data from a German asthma family study. The results based on the paired Hotelling's T(2) statistic tests confirm the previous findings. However, the paired Hotelling's T(2) tests produce much smaller P-values than those of the previous study. The permutation tests produce similar results to those of the previous study; moreover, additional marker combinations are shown to be significant by permutation tests. The proposed paired Hotelling's T(2) statistic tests are potentially powerful in mapping complex diseases. A SAS Macro, Hotel_fam.sas, has been written to implement the method for data analysis.
For population case-control association studies, the false-positive rates can be high due to inappropriate controls, which can occur if there is population admixture or stratification. Moreover, it is not always clear how to choose appropriate controls. Alternatively, the parents or normal sibs can be used as controls of affected sibs. For late-onset complex diseases, parental data are not usually available. One way to study late-onset disorders is to perform sib-pair or sibship analyses. This paper proposes sibship-based Hotelling's T2 test statistics for high-resolution linkage disequilibrium mapping of complex diseases. For a sample of sibships, suppose that each sibship consists of at least one affected sib and at least one normal sib. Assume that genotype data of multiple tightly linked markers/haplotypes are available for each individual in the sample. Paired Hotelling's T2 test statistics are proposed for high-resolution association studies using normal sibs as controls for affected sibs, based on two coding methods: 'haplotype/allele coding' and 'genotype coding'. The paired Hotelling's T2 tests take into account not only the correlation among the markers, but also take the correlation within each sib-pair. The validity of the proposed method is justified by rigorous mathematical and statistical proofs under the large sample theory. The non-centrality parameter approximations of the test statistics are calculated for power and sample size calculations. By carrying out power and simulation studies, it was found that the non-centrality parameter approximations of the test statistics were accurate. By power and type I error analysis, the test statistics based on the 'haplotype/allele coding' method were found to be advantageous in comparison to the test statistics based on the 'genotype coding' method. The test statistics based on multiple markers can have higher power than those based on a single marker. The test statistics can be applied not only for bi-allelic markers, but also for multi-allelic markers. In addition, the test statistics can be applied to analyse the genetic data of multiple markers which contain double heterozygotes--that is, unknown linkage phase data. An SAS macro, Hotel_sibs.sas, is written to implement the method for data analysis.
Haplotypes--that is, linear arrangements of alleles on the same chromosome that were inherited as a unit--are expected to carry important information in the context of association fine mapping of complex diseases. In consideration of a set of tightly linked markers, there is an enormous number of different marker combinations that can be analyzed. Therefore, a severe multiple-testing problem is introduced. One method to deal with this problem is Bonferroni correction by the number of combinations that are considered. Bonferroni correction is appropriate for independent tests but will result in a loss of power in the presence of linkage disequilibrium in the region. A second method is to perform simulations. It is unfortunate that most methods of haplotype analysis already require simulations to obtain an uncorrected P value for a specific marker combination. Thus, it seems that nested simulations are necessary to obtain P values that are corrected for multiple testing, which, apparently, limits the applicability of this approach because of computer running-time restrictions. Here, an algorithm is described that avoids such nested simulations. We check the validity of our approach under two disease models for haplotype analysis of family data. The true type I error rate of our algorithm corresponds to the nominal significance level. Furthermore, we observe a strong gain in power with our method to obtain the global P value, compared with the Bonferroni procedure to calculate the global P value. The method described here has been implemented in the latest update of our program FAMHAP.
The synchrotron powder diffraction beamline B2 at HASYLAB/DESY is described. The beamline is capable of high-resolution powder diffraction as well as time-resolved studies and offers several sophisticated ancillary equipments for special applications. A newly developed image-plate system allows for kinetic studies with good resolution in the minutes range. Numerous sample environments allow for various standard applications including structure solution, kinetic studies and in situ observations under flexible and well defined conditions. Representative examples are shown for these setups, which are also supported for experiments of external users.