The role of metabolic syndrome (MetS) as a preceding metabolic state for type 2 diabetes and cardiovascular disease is widely recognised. To accumulate knowledge of the pathological mechanisms behind ...the condition at the methylation level, we conducted an epigenome-wide association study (EWAS) of MetS and its components, testing 1187 individuals of European ancestry for approximately 470 000 methylation sites throughout the genome. Methylation site cg19693031 in gene TXNIP -previously associated with type 2 diabetes, glucose and lipid metabolism, associated with fasting glucose level (P = 1.80 × 10
). Cg06500161 in gene ABCG1 associated both with serum triglycerides (P = 5.36 × 10
) and waist circumference (P = 5.21 × 10
). The previously identified type 2 diabetes-associated locus cg08309687 in chromosome 21 associated with waist circumference for the first time (P = 2.24 × 10
). Furthermore, a novel HDL association with cg17901584 in chromosome 1 was identified (P = 7.81 × 10
). Our study supports previous genetic studies of MetS, finding that lipid metabolism plays a key role in pathology of the syndrome. We provide evidence regarding a close interplay with glucose metabolism. Finally, we suggest that in attempts to identify methylation loci linking separate MetS components, cg19693031 appears to represent a strong candidate.
Although many biotechnological advancements have been made in the past decade, there has been very limited success in unraveling the genetic component of complex traits. Heavily invested research has ...been initiated based on etiological models of unrealistic simplicity and conducted under poor experimental designs, on data sets of insufficient size, leading to an overestimation of the effect sizes of genetic variants and the quantity and quality of linkage disequilibrium (LD). Arguments about whether families or unrelated individuals provide more power for gene mapping have been erroneously debated as issues of whether linkage or LD are more detectable sorts of correlation. Although the latter issue may be subject to debate, there is no doubt that family-based analysis is more powerful for detecting linkage and/or LD. If the recent advances in biotechnology are to be exploited effectively, vastly improved study designs will be imperative, as the reasons for the lack of success to date have much more to do with biology than technology, an issue that has become increasingly clear with the findings of the past years.
Despite biotechnological advances, we have made very little progress in understanding the genetic components of complex diseases. Temptations to plan future research directions based on the hype surrounding the ‘post-genomic euphoria’ rather than substantive scientific argument must be carefully avoided.
Life is a simulation of life – or is it? Weiss, Kenneth; Hiekkalinna, Tero
Evolutionary anthropology,
July/August 2017, 20170701, Letnik:
26, Številka:
4
Journal Article
Diabetic nephropathy (DN) affects about 30% of patients with type 1 diabetes (T1D) and contributes to serious morbidity and mortality. So far only the 3q21-q25 region has repeatedly been indicated as ...a susceptibility region for DN. The aim of this study was to search for new DN susceptibility loci in Finnish, Danish and French T1D families.
We performed a genome-wide linkage study using 384 microsatellite markers. A total of 175 T1D families were studied, of which 94 originated from Finland, 46 from Denmark and 35 from France. The whole sample set consisted of 556 individuals including 42 sib-pairs concordant and 84 sib-pairs discordant for DN. Two-point and multi-point non-parametric linkage analyses were performed using the Analyze package and the MERLIN software. A novel DN locus on 22q11 was identified in the joint analysis of the Finnish, Danish and French families by genome-wide multipoint non-parametric linkage analysis using the Kong and Cox linear model (NPL(pairs) LOD score 3.58). Nominal or suggestive evidence of linkage to this locus was also detected when the three populations were analyzed separately. Suggestive evidence of linkage was found to six additional loci in the Finnish and French sample sets.
This study identified a novel DN locus at chromosome 22q11 with significant evidence of linkage to DN. Our results suggest that this locus may be of importance in European populations. In addition, this study supports previously indicated DN loci on 3q21-q25 and 19q13.
In recent years, many genomewide screens have been performed, to identify novel loci predisposing to various complex diseases. Often, only a portion of the collected clinical data from the study ...subjects is used in the actual analysis of the trait, and much of the phenotypic data is ignored. With proper consent, these data could subsequently be used in studies of common quantitative traits influencing human biology, and such a reanalysis method would be further justified by the nonbiased ascertainment of study individuals. To make our point, we report here a quantitative-trait-locus (QTL) analysis of body-mass index (BMI) and stature (i.e., height), with genotypic data from genome scans of five Finnish study groups. The combined study group was composed of 614 individuals from 247 families. Five study groups were originally ascertained in genetic studies on hypertension, obesity, osteoarthritis, migraine, and familial combined hyperlipidemia. Most of the families are from the Finnish Twin Cohort, which represents a population-wide sample. In each of the five genome scans, ∼350 evenly spaced markers were genotyped on 22 autosomes. In analyzing the genotype data by a variance-component method, we found, on chromosome 7pter (maximum multipoint LOD score of 2.91), evidence for QTLs affecting stature, and a second locus, with suggestive evidence for linkage to stature, was detected on chromosome 9q (maximum multipoint LOD score of 2.61). Encouragingly, the locus on chromosome 7 is supported by the data reported by Hirschhorn et al. (in this issue), who used a similar method. We found no evidence for QTLs affecting BMI.
To review, on a genome-wide scale, a linkage result obtained in an earlier candidate gene analysis in this same study sample, and to look for other possible contributing genetic loci predisposing to ...hypertension in this population.
An affected sibpair linkage study with highly polymorphic genetic markers spanning the genome at an average intermarker density of 10 cM.
A total of 47 families with two affected siblings (mostly dizygotic twins) and all available additional family members from the genetic isolate of Finland. The families were identified through the Finnish Twin Cohort Study, the total number of this follow-up cohort being 13,888. The study sample was selected on the basis of early-onset hypertension with minimal presence of other phenotypic risk factors such as obesity.
The AT1 locus stood out as the most significant locus in this population (maximum likelihood score 4.04). Some evidence for linkage was also detected with markers on chromosomes 2q (maximum likelihood score 2.96), 22q (2.07), and Xp (2.41).
Our results establish the role of the AT1 locus, on a genome-wide scale, as a major contributing locus to essential hypertension in this study sample.
•Two respondent subgroups based on flavor preferences were identified.•One subgroup favored sour and spicy foods and responded favorably to capsaicin.•The same group showed less tendency for food ...neophobia.•Genetic variability partially explained the subgroups.
Subgroups based on flavor preferences were identified and their genetic and behavior related characteristics investigated using extensive data from 331 Finnish twins (21–25years, 146 men) including 47 monozygotic (MZ) and 93 dizygotic (DZ) pairs, and 51 twin individuals. The subgroup identification (hierarchical and K-means clustering) was based on liking responses to food names representing sour, umami, and spicy flavor qualities. Furthermore, sensory tests were conducted, a questionnaire on food likes completed, and various eating behavior related traits measured with validated scales. Sensory data included intensity ratings of PROP (6-n-propylthiouracil-impregnated filter paper), hedonic and intensity responses to sourness (orange juice with and without added citric acid, 0.42%), pungency (strawberry jelly with and without added capsaicin 0.00013%) and umami (‘mouthfeel flavor’ taste solution). Ratings of liking of 41 general food names were categorized into salty-and-fatty, sweet-and-fatty, fruits and vegetables and fish foods. Subgroup differences (complex samples procedure) and the genetics underlying the subgroups (structural equation modeling) were investigated. Of the resulting two groups (basic, n=140, adventurous n=152; non-grouped n=39), the adventurous expressed higher liking for sour and spicy foods, and had more tolerance for capsaicin burn in the sensory-hedonic test. The adventurous were also less food neophobic (25.9±9.1 vs. 32.5±10.6, respectively) and expressed higher liking for fruits and vegetables compared to the basic group. Genetic effects were shown to underlie the subgroups (heritability 72%, CI: 36–92%). Linkage analysis for 27 candidate gene regions revealed suggestively that being adventurous is linked to TAS1R1 and PKD1L3 genes. These results indicate that food neophobia and genetic differences may form a barrier through which individual flavor preferences are generated.
Research in modern biomedicine and social science requires sample sizes so large that they can often only be achieved through a pooled co-analysis of data from several studies. But the pooling of ...information from individuals in a central database that may be queried by researchers raises important ethico-legal questions and can be controversial. In the UK this has been highlighted by recent debate and controversy relating to the UK's proposed 'care.data' initiative, and these issues reflect important societal and professional concerns about privacy, confidentiality and intellectual property. DataSHIELD provides a novel technological solution that can circumvent some of the most basic challenges in facilitating the access of researchers and other healthcare professionals to individual-level data.
Commands are sent from a central analysis computer (AC) to several data computers (DCs) storing the data to be co-analysed. The data sets are analysed simultaneously but in parallel. The separate parallelized analyses are linked by non-disclosive summary statistics and commands transmitted back and forth between the DCs and the AC. This paper describes the technical implementation of DataSHIELD using a modified R statistical environment linked to an Opal database deployed behind the computer firewall of each DC. Analysis is controlled through a standard R environment at the AC.
Based on this Opal/R implementation, DataSHIELD is currently used by the Healthy Obese Project and the Environmental Core Project (BioSHaRE-EU) for the federated analysis of 10 data sets across eight European countries, and this illustrates the opportunities and challenges presented by the DataSHIELD approach.
DataSHIELD facilitates important research in settings where: (i) a co-analysis of individual-level data from several studies is scientifically necessary but governance restrictions prohibit the release or sharing of some of the required data, and/or render data access unacceptably slow; (ii) a research group (e.g. in a developing nation) is particularly vulnerable to loss of intellectual property-the researchers want to fully share the information held in their data with national and international collaborators, but do not wish to hand over the physical data themselves; and (iii) a data set is to be included in an individual-level co-analysis but the physical size of the data precludes direct transfer to a new site for analysis.
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