FADS Gene Cluster Polymorphisms: Important Modulators of Fatty Acid Levels and Their Impact on Atopic Diseases

Long-chain polyunsaturated fatty acids (LC-PUFAs) play an important role in several physiological processes and their concentration in phospholipids has been associated with several complex diseases, such as atopic disease. The level and composition of LC-PUFAs in the human body is highly dependent on their intake in the diet or on the intake of fatty acid precursors, which are endogenously elongated and desaturated to physiologically active LC-PUFAs. The most important enzymes in this reaction cascade are the Delta(5) and Delta(6) desaturase. Several studies in the last few years have revealed that single nucleotide polymorphisms (SNPs) in the 2 desaturase encoding genes (FADS1 and FADS2) are highly associated with the concentration of omega-6 and omega-3 fatty acids, showing that beside nutrition, genetic factors also play an important role in the regulation of LC-PUFAs. This review focuses on current knowledge of the impact of genetic polymorphisms on LC-PUFA metabolism and on their potential role in the development of atopic diseases. Copyright (c) 2009 S. Karger AG, Base

A novel GJA8 mutation causing a recessive triangular cataract

The aim of the study was to characterize the underlying mutation in a consanguineous family having cataracts. METHODS: Family D having congenital cataracts was treated at the University Eye Clinics at Giessen (Germany). Lens material from surgeries was collected, immediately frozen at -80 degrees C, and used for cDNA production. Blood was taken from the proband and available family members. Polymerase chain reaction (PCR)-amplified DNA fragments were characterized by sequencing and restriction digestion. RESULTS: The proband, AD, has a dense, triangular nuclear cataract. The parents are consanguineous, and the mother and grandmother suffer from a discrete, symmetric opacity of the fetal lens nucleus. The proband's lens cDNA showed a homozygous insertion of one G after position 776 of the GJA8 gene, leading to a frame shift and 123 novel amino acids. The homozygous mutation was confirmed in the genomic DNA and is also present in the cataract-operated brother of the proband; all other family members investigated were heterozygous. The mutation could not be detected in 96 healthy controls from Germany. CONCLUSIONS: The ins776G mutation most likely causes a recessive triangular cataract with variable expressivity of a weak phenotype in heterozygotes

Gene-Gene Interaction between APOA5 and USF1: Two Candidate Genes for the Metabolic Syndrome

Objective: The metabolic syndrome, a major cluster of risk factors for cardiovascular diseases, shows increasing prevalence worldwide. Several studies have established associations of both apolipoprotein A5 (APOA5) gene variants and upstream stimulatory factor 1 (USF1) gene variants with blood lipid levels and metabolic syndrome. USF1 is a transcription factor for APOA5. Methods: We investigated a possible interaction between these two genes on the risk for the metabolic syndrome, using data from the German population-based KORA survey 4 (1,622 men and women aged 55-74 years). Seven APOA5 single nucleotide polymorphisms (SNPs) were analyzed in combination with six USF1 SNPs, applying logistic regression in an additive model adjusting for age and sex and the definition for metabolic syndrome from the National Cholesterol Education Program's Adult Treatment Panel III (NCEP (AIII)) including medication. Results: The overall prevalence for metabolic syndrome was 41%. Two SNP combinations showed a nominal gene-gene interaction (p values 0.024 and 0.047). The effect of one SNP was modified by the other SNP, with a lower risk for the metabolic syndrome with odds ratios (ORs) between 0.33 (95% CI = 0.13-0.83) and 0.40 (95% CI = 0.15-1.12) when the other SNP was homozygous for the minor allele. Nevertheless, none of the associations remained significant after correction for multiple testing. Conclusion: Thus, there is an indication of an interaction between APOA5 and USF1 on the risk for metabolic syndrome

Mutation analysis in a German family identified a new cataract-causing allele in the CRYBB2 gene

The study demonstrates the functional candidate gene analysis in a cataract family of German descent. METHODS: We screened a German family, clinically documented to have congenital cataracts, for mutation in the candidate genes CRYG (A to D) and CRYBB2 through polymerase chain reaction analyses and sequencing. RESULTS: Congenital cataract was first observed in a daughter of healthy parents. Her two children (a boy and a girl) also suffer from congenital cataracts and have been operated within the first weeks of birth. Morphologically, the cataract is characterized as nuclear with an additional ring-shaped cortical opacity. Molecular analysis revealed no causative mutation in any of the CRYG genes. However, sequencing of the exons of the CRYBB2 gene identified a sequence variation in exon 5 (383 A>T) with a substitution of Asp to Val at position 128. All three affected family members revealed this change but it was not observed in any of the unaffected persons of the family. The putative mutation creates a restriction site for the enzyme TaiI. This mutation was checked for in controls of randomly selected DNA samples from ophthalmologically normal individuals from the population-based KORA S4 study (n=96) and no mutation was observed. Moreover, the Asp at position 128 is within a stretch of 12 amino acids, which are highly conserved throughout the animal kingdom. For the mutant protein, the isoelectric point is raised from pH 6.50 to 6.75. Additionally, the random coil structure of the protein between the amino acids 126-139 is interrupted by a short extended strand structure. In addition, this region becomes hydrophobic (from neutral to +1) and the electrostatic potential in the region surrounding the exchanged amino acid alters from a mainly negative potential to an enlarged positive potential. CONCLUSIONS: The D128V mutation segregates only in affected family members and is not seen in representative controls. It represents the first mutation outside exon 6 of the human CRYBB2 gene

How to analyze many contingency tables simultaneously in genetic association studies

We study exact tests for (2 x 2) and (2 x 3) contingency tables, in particular exact chi-squared tests and exact tests of Fisher type. In practice, these tests are typically carried out without randomization, leading to reproducible results but not exhausting the significance level. We discuss that this can lead to methodological and practical issues in a multiple testing framework when many tables are simultaneously under consideration as in genetic association studies.Realized randomized p-values are proposed as a solution which is especially useful for data-adaptive (plug-in) procedures. These p-values allow to estimate the proportion of true null hypotheses much more accurately than their non-randomized counterparts. Moreover, we address the problem of positively correlated p-values for association by considering techniques to reduce multiplicity by estimating the "effective number of tests" from the correlation structure.An algorithm is provided that bundles all these aspects, efficient computer implementations are made available, a small-scale simulation study is presented and two real data examples are show

A comparison of curated gene sets versus transcriptomics-derived gene signatures for detecting pathway activation in immune cells

Background: Despite the significant contribution of transcriptomics to the fields of biological and biomedical research, interpreting long lists of significantly differentially expressed genes remains a challenging step in the analysis process. Gene set enrichment analysis is a standard approach for summarizing differentially expressed genes into pathways or other gene groupings. Here, we explore an alternative approach to utilizing gene sets from curated databases. We examine the method of deriving custom gene sets which may be relevant to a given experiment using reference data sets from previous transcriptomics studies. We call these data-derived gene sets, "gene signatures" for the biological process tested in the previous study. We focus on the feasibility of this approach in analyzing immune-related processes, which are complicated in their nature but play an important role in the medical research. Results: We evaluate several statistical approaches to detecting the activity of a gene signature in a target data set. We compare the performance of the data-derived gene signature approach with comparable GO term gene sets across all of the statistical tests. A total of 61 differential expression comparisons generated from 26 transcriptome experiments were included in the analysis. These experiments covered eight immunological processes in eight types of leukocytes. The data-derived signatures were used to detect the presence of immunological processes in the test data with modest accuracy (AUC = 0.67). The performance for GO and literature based gene sets was worse (AUC = 0.59). Both approaches were plagued by poor specificity. Conclusions: When investigators seek to test specific hypotheses, the data-derived signature approach can perform as well, if not better than standard gene-set based approaches for immunological signatures. Furthermore, the data-derived signatures can be generated in the cases that well-defined gene sets are lacking from pathway databases and also offer the opportunity for defining signatures in a cell-type specific manner. However, neither the data-derived signatures nor standard gene-sets can be demonstrated to reliably provide negative predictions for negative cases. We conclude that the data-derived signature approach is a useful and sometimes necessary tool, but analysts should be weary of false positives. © 2020 The Author(s)

Discovery of Sexual Dimorphisms in Metabolic and Genetic Biomarkers

Metabolomic profiling and the integration of whole-genome genetic association data has proven to be a powerful tool to comprehensively explore gene regulatory networks and to investigate the effects of genetic variation at the molecular level. Serum metabolite concentrations allow a direct readout of biological processes, and association of specific metabolomic signatures with complex diseases such as Alzheimer's disease and cardiovascular and metabolic disorders has been shown. There are well-known correlations between sex and the incidence, prevalence, age of onset, symptoms, and severity of a disease, as well as the reaction to drugs. However, most of the studies published so far did not consider the role of sexual dimorphism and did not analyse their data stratified by gender. This study investigated sex-specific differences of serum metabolite concentrations and their underlying genetic determination. For discovery and replication we used more than 3,300 independent individuals from KORA F3 and F4 with metabolite measurements of 131 metabolites, including amino acids, phosphatidylcholines, sphingomyelins, acylcarnitines, and C6-sugars. A linear regression approach revealed significant concentration differences between males and females for 102 out of 131 metabolites (p-values<3.8 x 10(-4); Bonferroni-corrected threshold). Sex-specific genome-wide association studies (GWAS) showed genome-wide significant differences in beta-estimates for SNPs in the CPS1 locus (carbamoyl-phosphate synthase 1, significance level: p<3.8 x 10(-10); Bonferroni-corrected threshold) for glycine. We showed that the metabolite profiles of males and females are significantly different and, furthermore, that specific genetic variants in metabolism-related genes depict sexual dimorphism. Our study provides new important insights into sex-specific differences of cell regulatory processes and underscores that studies should consider sex-specific effects in design and interpretation

Unifying candidate gene and GWAS Approaches in Asthma.

The first genome wide association study (GWAS) for childhood asthma identified a novel major susceptibility locus on chromosome 17q21 harboring the ORMDL3 gene, but the role of previous asthma candidate genes was not specifically analyzed in this GWAS. We systematically identified 89 SNPs in 14 candidate genes previously associated with asthma in >3 independent study populations. We re-genotyped 39 SNPs in these genes not covered by GWAS performed in 703 asthmatics and 658 reference children. Genotyping data were compared to imputation data derived from Illumina HumanHap300 chip genotyping. Results were combined to analyze 566 SNPs covering all 14 candidate gene loci. Genotyped polymorphisms in ADAM33, GSTP1 and VDR showed effects with p-values <0.0035 (corrected for multiple testing). Combining genotyping and imputation, polymorphisms in DPP10, EDN1, IL12B, IL13, IL4, IL4R and TNF showed associations at a significance level between p = 0.05 and p = 0.0035. These data indicate that (a) GWAS coverage is insufficient for many asthma candidate genes, (b) imputation based on these data is reliable but incomplete, and (c) SNPs in three previously identified asthma candidate genes replicate in our GWAS population with significance after correction for multiple testing in 14 genes

Associations between BMI and the FTO Gene Are Age Dependent: Results from the GINI and LISA Birth Cohort Studies up to Age 6 Years

Objective: The association between polymorphisms in intron 1 of the fat mass and obesity associated gene (FTO) and obesity-related traits is one of the most robust associations reported for complex traits and is established both in adults and children. However, little is known about the longitudinal dynamics of these polymorphisms on body mass index (BMI), overweight, and obesity. Methods: This study is based on the 2,732 full-term neonates of the German GINI-plus and LISA-plus birth cohorts, for whom genotyping data on the FTO variants rs1558902 (T>A) or rs9935401 (G>A) were available. Children were followed from birth up to age 6 years. Up to 9 anthropometric measurements of BMI were obtained. Fractional-Polynomial-Generalized-Estimation-Equation modeling was used to assess developmental trends and their potential dependence on genotype status. Results: We observed no evidence for BMI differences between genotypes of both variants for the first 3 years of life. However, from age 3 years onwards, we noted a higher BMI for the homozygous minor alleles carriers in comparison to the other two genotype groups. However, evidence for statistical significance was reached from the age of 4 years onwards. Conclusions: This is one of the first studies investigating in detail the development of BMI depending on FTO genotype between birth and the age of 6 years in a birth cohort not selected for the phenotype studied. We observed that the association between BMI and FTO genotype evolves gradually and becomes descriptively detectable from the age of 3 years onwards

BMI at Age 8 Years Is Influenced by the Type 2 Diabetes Susceptibility Genes HHEX-IDE and CDKAL1

OBJECTIVE: To determine whether HHEX-IDE and CDKAL1 genes, which are associated with birth weight and susceptibility to type 2 diabetes, continue to influence growth during childhood. RESEARCH DESIGN AND METHODS: BMI, weight, and height at age 8 years expressed as age- and sex-corrected standard deviation scores (SDS) against national reference data and single-nucleotide polymorphism genotyping of HHEX-IDE and CDKAL1 loci were analyzed in 646 prospectively followed children in the German BABYDIAB cohort. All children were singleton full-term births; 386 had mothers with type 1 diabetes, and 260 had fathers with type 1 diabetes and a nondiabetic mother. RESULTS: Type 2 diabetes risk alleles at the HHEX-IDE locus were associated with reduced BMI-SDS at age 8 years (0.17 SDS per allele; P = 0.004). After stratification for birth weight, both HHEX-IDE and CDKAL1 risk alleles were associated with reduced BMI-SDS (0.45 SDS, P = 0.0002; 0.52 SDS, P = 0.0001) and weight-SDS (0.22 SDS, P = 0.04; 0.56 SDS, P = 0.0002) in children born large for gestational age (&gt;90th percentile) but not children born small or appropriate for gestational age. Within children born large for gestational age, BMI and weight decreased with each additional type 2 diabetes risk allele ( approximately -2 kg per allele; &gt;8 kg overall). Findings were consistent in children of mothers with type 1 diabetes (P &lt; 0.0001) and children of nondiabetic mothers (P = 0.008). CONCLUSIONS: The type 2 diabetes susceptibility alleles at HHEX-IDE and CDKAL1 loci are associated with low BMI at age 8 years in children who were born large for gestational age