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Genome-wide association analysis on monozygotic twin-pairs offers a route to discovery of gene–environment interactions through testing for variability loci associated with sensitivity to individual environment/lifestyle. We present a genome-wide scan of loci associated with intra-pair differences in serum lipid and apolipoprotein levels. We report data for 1,720 monozygotic female twin-pairs from GenomEUtwin project with 2.5 million SNPs, imputed or genotyped, and measured serum lipid fractions for both twins. We found one locus associated with intra-pair differences in high-density lipoprotein cholesterol, rs2483058 in an intron of SRGAP2, where twins carrying the C allele are more sensitive to environmental factors (P = 3.98 × 10−8). We followed up the association in further genotyped monozygotic twins (N = 1,261), which showed a moderate association for the variant (P = 0.200, same direction of an effect). In addition, we report a new association on the level of apolipoprotein A-II (P = 4.03 × 10−8).
Genome-wide linkage analysis using multiple traits and statistical software packages is a tedious process which requires a significant amount of manual file manipulation. Different linkage analysis programs require different input file formats, making the task of analyzing data with multiple methods even more time-consuming. We have developed a software tool, AUTOGSCAN, that automates file formatting, the running of statistical analyses, and the summarizing of resulting statistics for whole genome scans with a push of a button, using several independent, and often idiosyncratic, statistical software packages such as MERLIN, SOLAR and GENEHUNTER. We also describe a program, ANALYZE, designed to run qualitative linkage analysis with several different statistical strategies and programs to efficiently screen for linkage and linkage disequilibrium for a given discrete trait. The ANALYZE program can also be used by AUTOGSCAN in a genome-wide sense.
The aim of this study was to examine whether maximal walking speed, maximal isometric muscle strength, leg extensor power and lower leg muscle cross-sectional area (CSA) shared a genetic effect in common. In addition, we wanted to identify the chromosomal areas linked to maximal walking speed and these muscle characteristics and also investigate whether maximal walking speed and these three skeletal muscle characteristics are regulated by the same chromosomal areas. We studied 217 monozygotic (MZ) and dizygotic (DZ) female twin pairs aged 66 to 75 years in the Finnish Twin Study on Aging study. The DZ pairs (94) were genotyped for 397 microsatellite markers in 22 autosomes and X-chromosome. Genetic modeling showed that, muscle CSA, strength, power and walking speed shared a genetic effect in common which accounted for 7% of the variation in CSA, 51% in strength, 37% in power and 35% in walking speed. The results of an explorative multipoint linkage analysis suggested that the highest LOD score found for each phenotype was 2.41 for walking speed on chromosome 13q22.1, 2.14 for strength on chromosome 15q14, 2.84 for power on chromosome 8q24.23, and 2.93 for muscle CSA on chromosome 20q13.31. Also a suggestive LOD score, 2.68, for muscle CSA was found on chromosome 9q34.3. The chromosomal areas of a suggestive linkage for strength and power partly overlapped LOD scores higher than 1.0 being seen for these phenotypes on chromosome 15. The present study was the first genome-wide linkage analysis to be conducted for these multifactorial and clinically important phenotypes underlying functional independence in older women.
The amount of available DNA is often a limiting factor in pursuing genetic analyses of large-scale population cohorts. An association between higher DNA yield from blood and several phenotypes associated with inflammatory states has recently been demonstrated, suggesting that exclusion of samples with very low DNA yield may lead to biased results in statistical analyses. Whole genome amplification (WGA) could present a solution to the DNA concentration-dependent sample selection. The aim was to thoroughly assess WGA for samples with low DNA yield, using the multiply-primed rolling circle amplification method. Fifty-nine samples were selected with the lowest DNA yield (less than 7.5µg) among 799 samples obtained for one population cohort. The genotypes obtained from two replicate WGA samples and the original genomic DNA were compared by typing 24 single nucleotide polymorphisms (SNPs). Multiple genotype discrepancies were identified for 13 of the 59 samples. The largest portion of discrepancies was due to allele dropout in heterozygous genotypes in WGA samples. Pooling the WGA DNA replicates prior to genotyping markedly improved genotyping reproducibility for the samples, with only 7 discrepancies identified in 4 samples. The nature of discrepancies was mostly homozygote genotypes in the genomic DNA and heterozygote genotypes in the WGA sample, suggesting possible allele dropout in the genomic DNA sample due to very low amounts of DNA template. Thus, WGA is applicable for low DNA yield samples, especially if using pooled WGA samples. A higher rate of genotyping errors requires that increased attention be paid to genotyping quality control, and caution when interpreting results.
Amajor component of variation in body height is due to genetic differences, but environmental factors have a substantial contributory effect. In this study we aimed to analyse whether the genetic architecture of body height varies between affluent western societies. We analysed twin data from eight countries comprising 30,111 complete twin pairs by using the univariate genetic model of the Mx statistical package. Body height and zygosity were self-reported in seven populations and measured directly in one population. We found that there was substantial variation in mean body height between countries; body height was least in Italy (177 cm in men and 163 cm in women) and greatest in the Netherlands (184 cm and 171 cm, respectively). In men there was no corresponding variation in heritability of body height, heritability estimates ranging from 0.87 to 0.93 in populations under an additive genes/unique environment (AE) model. Among women the heritability estimates were generally lower than among men with greater variation between countries, ranging from 0.68 to 0.84 when an additive genes/shared environment/unique environment (ACE) model was used. In four populations where an AE model fit equally well or better, heritability ranged from 0.89 to 0.93. This difference between the sexes was mainly due to the effect of the shared environmental component of variance, which appears to be more important among women than among men in our study populations. Our results indicate that, in general, there are only minor differences in the genetic architecture of height between affluent Caucasian populations, especially among men.
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