A Genetic Epidemiological Study of Behavioral Traits

Human behavioural genetics aims to unravel the genetic and environmental contributions to variations in human behaviour. Behaviour is a complex trait, involving multiple genes that are affected by a variety of other factors. Genetic epidemiological research of behaviour goes back to Sir Francis Galton (1822-1911), who systematically studied heredity of human behaviour and mind, introducing major statistical concepts such as correlation and regression towards the mean. After a brief period in which genetic research of behaviour fell into dismay as a result of its association to eugenics and the Nazi regime, there is at present growing scientific interest in genes and behaviour. Without a doubt, behaviour in humans and animals is for a large part genetically determined1. In this thesis, I have limited myself to a number of diseases and traits

A Genomic Background Based Method for Association Analysis in Related Individuals

Background. Feasibility of genotyping of hundreds and thousands of single nucleoticle polymorphisms (SNPs) in thousands of study subjects have triggered the need for fast, powerful, and reliable methods for genome-wide association analysis. Here we consider a situation when study participants are genetically related (e.g. due to systematic sampling of families or because a study was performed in a genetically isolated population). Of the available methods that account for relatedness, the Measured Genotype (MG) approach is considered the 'gold standard'. However, MG is not efficient with respect to time taken for the analysis of genome-wide data. In this context we proposed a fast two-step method called Genome-wide Association using Mixed Model and Regression (GRAMMAR) for the analysis of pedigree-based quantitative traits. This method certainly overcomes the drawback of time limitation of the measured genotype (MG) approach, but pays in power. One of the major drawbacks of both MG and GRAMMAR, is that they crucially depend on the availability of complete and correct pedigree data, which is rarely available. Methodology. In this study we first explore type 1 error and relative power of MG, GRAMMAR, and Genomic Control (GCC) approaches for genetic association analysis. Secondly, we propose an extension to GRAMMAR i.e. GRAMMAR-GC. Finally, we propose application of GRAMMAR-GC using the kinship matrix estimated through genomic marker data, instead of (possibly missing and/or incorrect) genealogy. Conclusion. Through simulations we show that MG approach maintains high power across a range of heritabilities and possible pedigree structures, and always outperforms other contemporary methods. We also show that the power of our proposed GRAMMAR-GC approaches to that of the 'gold standard' MG for all models and pedigrees studied. We show that this method is both feasible and powerful and has correct type 1 error in the context of genome-wide association analysis in related individuals

Linkage analysis and whole exome sequencing identify a novel candidate gene in a Dutch multiple sclerosis family

Background: Multiple sclerosis (MS) is a complex disease resulting from the joint effect of many genes. It has been speculated that rare variants might explain part of the missing heritability of MS. Objective: To identify rare coding genetic variants by analyzing a large MS pedigree with 11 affected individuals in several generations. Methods: Genome-wide linkage screen and whole exome sequencing (WES) were performed to identify novel coding variants in the shared region(s) and in the known 110 MS risk loci. The candidate variants were then assessed in 591 MS patients and 3169 controls. Results: Suggestive evidence for linkage was obtained to 7q11.22-q11.23. In WES data, a rare missense variant p.R183C in FKBP6 was identified that segregated with the disease in this family. The minor allele frequency was higher in an independent cohort of MS patients than in healthy controls (1.27% vs 0.95%), but not significant (odds ratio (OR) = 1.33 (95% confidence interval (CI): 0.8–2.4), p = 0.31). Conclusion: The rare missense variant in FKBP6 was identified in a large Dutch MS family segregating with the disease. This association to MS was not found in an independent MS cohort. Overall, genome-wide studies in larger cohorts are needed to adequately investigate the role of rare variants in MS risk

Candidate Gene-Based Association Study of Antipsychotic-Induced Movement Disorders in Long-Stay Psychiatric Patients: A Prospective Study

OBJECTIVE: Four types of antipsychotic-induced movement disorders: tardive dyskinesia (TD), parkinsonism, akathisia and tardive dystonia, subtypes of TD (orofacial and limb truncal dyskinesia), subtypes of parkinsonism (rest tremor, rigidity, and bradykinesia), as well as a principal-factor of the movement disorders and their subtypes, were examined for association with variation in 10 candidate genes (PPP1R1B, BDNF, DRD3, DRD2, HTR2A, HTR2C, COMT, MnSOD, CYP1A2, and RGS2). METHODS: Naturalistic study of 168 white long-stay patients with chronic mental illness requiring long-term antipsychotic treatment, examined by the same rater at least two times over a 4-year period, with a mean follow-up time of 1.1 years, with validated scales for TD, parkinsonism, akathisia, and tardive dystonia. The authors genotyped 31 SNPs, associated with movement disorders or schizophrenia in previous studies. Genotype and allele frequency comparisons were performed with multiple regression methods for continuous movement disorders. RESULTS: VARIOUS SNPS REACHED NOMINAL SIGNIFICANCE: TD and orofacial dyskinesia with rs6265 and rs988748, limb truncal dyskinesia with rs6314, rest tremor with rs6275, rigidity with rs6265 and rs4680, bradykinesia with rs4795390, akathisia with rs4680, tardive dystonia with rs1799732, rs4880 and rs1152746. After controlling for multiple testing, no significant results remained. CONCLUSIONS: The findings suggest that selected SNPs are not associated with a susceptibility to movement disorders. However, as the sample size was small and previous studies show inconsistent results, definite conclusions cannot be made. Replication is needed in larger study samples, preferably in longitudinal studies which take the fluctuating course of movement disorders and gene-environment interactions into account

Antipsychotic-Induced Movement Disorders in Long-Stay Psychiatric Patients and 45 Tag SNPs in 7 Candidate Genes: A Prospective Study

Objective: Four types of antipsychotic-induced movement disorders: tardive dyskinesia (TD), parkinsonism, akathisia and tardive dystonia, subtypes of TD (orofacial and limb truncal dyskinesia), subtypes of parkinsonism (rest tremor, rigidity, and bradykinesia), as well as a principal-factor of the movement disorders and their subtypes, were examined for association with variation in 7 candidate genes (GRIN2B, GRIN2A, HSPG2, DRD3, DRD4, HTR2C, and NQO1). Methods: Naturalistic study of 168 white long-stay patients with chronic mental illness requiring long-term antipsychotic treatment, examined by the same rater at least two times over a 4-year period, with a mean follow-up time of 1.1 years, with validated scales for TD, parkinsonism, akathisia, and tardive dystonia. The authors genotyped 45 tag SNPs in 7 candidate genes, associated with movement disorders or schizophrenia in previous studies. Genotype and allele frequency comparisons were performed with multiple regression methods for continuous movement disorders. Results: Various tag SNPs reached nominal significance; TD with rs1345423, rs7192557, r

Unveiling the Thermoelectric Performances of Zn1−xFexSe Nanoparticles Prepared by the Hydrothermal Method

Fe2+-doped ZnSe nanoparticles, with varying concentrations of Fe2+ dopants, were prepared by the hydrothermal method and investigated using a multi-technique approach exploiting scanning electron microscopy (SEM), X-ray diffraction (XRD), and Raman spectroscopy, as well as measurement of the electrical transport properties and Seebeck coefficient (S). The doped nanoparticles appeared as variable-sized agglomerates on nanocrystallites upon SEM investigation for any doping level. Combined XRD and Raman analyses revealed the occurrence of a cubic structure in the investigated samples. Electric and thermoelectric (TE) transport investigations showed an increase in TE performance with an increase in Fe atom concentrations, which resulted in an enhancement of the power factors from 13 µWm−1K−2 to 120 µWm−1K−2 at room temperature. The results were also dependent on the operating temperature. The maximum power factor of 9 × 10−3 Wm−1K−2 was achieved at 150 °C for the highest explored doping value. The possible applications of these findings were discussed

CYP1A2 and coffee intake and the modifying effect of sex, age, and smoking

Background: The enzyme CYP1A2 (cytochrome 1A2) is involved in the metabolism of certain drugs and caffeine, and its activity can be influenced by factors such as sex, age, and smoking. The single nucleotide polymorphism (SNP) rs762551A>C, which has also been studied for its modifying effect on cardiovascular disease, has been reported to alter enzyme activity. Objective: The objective was to study the effect of CYP1A2, sex, age, and smoking on coffee intake. Design: Within the Rotterdam Study, a population-based cohort, all coffee drinkers for whom genome-wide association data were available were selected. Because SNP rs762551 was not on the Illumina 550 platform, SNP rs2472299 was used as a proxy, with the A allele of rs762551 linked to the G allele of rs2472299. Linear regression analyses were used to determine the effect and interaction of rs2472299, sex, age, and smoking on coffee intake. Adjusted geometric means of coffee intake were calculated per genotype for the different smoking and sex strata by using multivariable general linear models. A combined analysis, with the use of a "risk score,"was performed to determine the contribution of each separate factor. Results: rs2472299G>A, female sex, and nonsmoking were significantly inversely related to coffee intake. Coffee intake was lowest in nonsmoking women homozygous for rs2472299G>A (3.49 cups/d; ∼436 mL). All factors contributed almost linearly to the intake of coffee, with the highest coffee intake in smoking men without the A allele (5.32 cups/d; ∼665 mL). Conclusion: rs2472299G>A, linked to rs762551A>C, sex, age, and smoking significantly contribute to coffee intake

Heritabilities, proportions of heritabilities explained by GWAS findings, and implications of cross-phenotype effects on PR interval

Electrocardiogram (ECG) measurements are a powerful tool for evaluating cardiac function and are widely used for the diagnosis and prediction of a variety of conditions, including myocardial infarction, cardiac arrhythmias, and sudden cardiac death. Recently, genome-wide association studies (GWASs) identified a large number of genes related to ECG parameter variability, specifically for the QT, QRS, and PR intervals. The aims of this study were to establish the heritability of ECG traits, including indices of left ventricular hypertrophy, and to directly assess the proportion of those heritabilities explained by GWAS variants. These analyses were conducted in a large, Dutch family-based cohort study, the Erasmus Rucphen Family study using variance component methods implemented in the SOLAR (Sequential Oligogenic Linkage Analysis Routines) software package. Heritability estimates ranged from 34 % for QRS and Cornell voltage product to 49 % for 12-lead sum. Trait-specific GWAS findings for each trait explained a fraction of their heritability (17 % for QRS, 4 % for QT, 2 % for PR, 3 % for Sokolow–Lyon index, and 4 % for 12-lead sum). The inclusion of all ECG-associated single nucleotide polymorphisms explained an additional 6 % of the heritability of PR. In conclusion, this study shows that, although GWAS explain a portion of ECG trait variability, a large amount of heritability remains to be explained. In addition, larger GWAS for PR are likely to detect loci already identified, particularly those observed for QRS and 12-lead sum