Supplementary data are available at Bioinformatics online.

Genome-wide association studies with moderate sample sizes are underpowered, especially when testing SNP alleles with low allele counts, a situation that may lead to high frequency of false-positive results and lack of replication in independent studies. Related individuals, such as twin pairs concordant for a disease, should confer increased power in genetic association analysis because of their genetic relatedness. We conducted a computer simulation study to explore the power advantage of the disease-concordant twin design, which uses singletons from disease-concordant twin pairs as cases and ordinary healthy samples as controls. We examined the power gain of the twin-based design for various scenarios (i.e., cases from monozygotic and dizygotic twin pairs concordant for a disease) and compared the power with the ordinary case-control design with cases collected from the unrelated patient population. Simulation was done by assigning various allele frequencies and allelic relative risks for different mode of genetic inheritance. In general, for achieving a power estimate of 80%, the sample sizes needed for dizygotic and monozygotic twin cases were one half and one fourth of the sample size of an ordinary case-control design, with variations depending on genetic mode. Importantly, the enriched power for dizygotic twins also applies to disease-concordant sibling pairs, which largely extends the application of the concordant twin design. Overall, our simulation revealed a high value of disease-concordant twins in genetic association studies and encourages the use of genetically related individuals for highly efficiently identifying both common and rare genetic variants underlying human complex diseases without increasing laboratory cost.

Hand grip strength is a measure of muscular strength and is used to study age-related loss of physical capacity. In order to explore the biological mechanisms that influence hand grip strength variation, an epigenome-wide association study (EWAS) of hand grip strength in 672 middle-aged and elderly monozygotic twins (age 55–90 years) was performed, using both individual and twin pair level analyses, the latter controlling the influence of genetic variation. Moreover, as measurements of hand grip strength performed over 8 years were available in the elderly twins (age 73–90 at intake), a longitudinal EWAS was conducted for this subsample. No genome-wide significant CpG sites or pathways were found, however two of the suggestive top CpG sites were mapped to the COL6A1 and CACNA1B genes, known to be related to muscular dysfunction. By investigating genomic regions using the comb-p algorithm, several differentially methylated regions in regulatory domains were identified as significantly associated to hand grip strength, and pathway analyses of these regions revealed significant pathways related to the immune system, autoimmune disorders, including diabetes type 1 and viral myocarditis, as well as negative regulation of cell differentiation. The genes contributing to the immunological pathways were HLA-B, HLA-C, HLA-DMA, HLA-DPB1, MYH10, ERAP1 and IRF8, while the genes implicated in the negative regulation of cell differentiation were IRF8, CEBPD, ID2 and BRCA1. In conclusion, this exploratory study suggests hand grip strength to associate with differentially methylated regions enriched in immunological and cell differentiation pathways, and hence merits further investigations.Electronic supplementary materialThe online version of this article (10.1007/s10522-019-09818-1) contains supplementary material, which is available to authorized users.

Background Previous studies have determined the epigenetic association between DNA methylation and pulmonary function among various ethnics, whereas this association is largely unknown in Chinese adults. Thus, we aimed to explore epigenetic relationships between genome-wide DNA methylation levels and pulmonary function among middle-aged Chinese monozygotic twins. Methods The monozygotic twin sample was drawn from the Qingdao Twin Registry. Pulmonary function was measured by three parameters including forced expiratory volume the first second (FEV1), forced vital capacity (FVC), and FEV1/FVC ratio. Linear mixed effect model was used to regress the methylation level of CpG sites on pulmonary function. After that, we applied Genomic Regions Enrichment of Annotations Tool (GREAT) to predict the genomic regions enrichment, and used comb-p python library to detect differentially methylated regions (DMRs). Gene expression analysis was conducted to validate the results of differentially methylated analyses. Results We identified 112 CpG sites with the level of P < 1 × 10–4 which were annotated to 40 genes. We identified 12 common enriched pathways of three pulmonary function parameters. We detected 39 DMRs located at 23 genes, of which PRDM1 was related to decreased pulmonary function, and MPL, LTB4R2, and EPHB3 were related to increased pulmonary function. The gene expression analyses validated DIP2C, ASB2, SLC6A5, and GAS6 related to decreased pulmonary function. Conclusion Our DNA methylation sequencing analysis on identical twins provides new references for the epigenetic regulation on pulmonary function. Several CpG sites, genes, biological pathways and DMRs are considered as possible crucial to pulmonary function.

Genetic interaction is a crucial issue in the understanding of functional pathways underlying complex diseases. However, detecting such interaction effects is challenging in terms of both methodology and statistical power. We address this issue by introducing a disease-concordant twin-case-only design, which applies to both monozygotic and dizygotic twins. To investigate the power, we conducted a computer simulation study by setting a series of parameter schemes with different minor allele frequencies and relative risks. Results from the simulation study reveals that the disease-concordant twin-caseonly design largely reduces sample size required for sufficient power compared to the ordinary case-only design for detecting gene-gene interaction using unrelated individuals. Sample sizes for dizygotic and monozygotic twins were roughly 1/2 and 1/4 of sample sizes in the ordinary case-only design. Since dizygotic twins are genetically similar as siblings, the enriched power for dizygotic twins also applies to affected siblings, which could help to largely extend the application of the powerful twin-case-only design. In summary, our simulation reveals high value of disease-concordant twins and siblings in efficiently detecting gene-by-gene interactions.