Epistasis (gene-gene interaction) is a ubiquitous component of the genetic architecture of complex traits such as susceptibility to common human diseases. Given the strong negative correlation between circulating adiponectin and resistin levels, the potential intermolecular epistatic interactions between ADIPOQ (SNP+45T > G, SNP+276G > T, SNP+639T > C and SNP+1212A > G) and RETN (SNP-420C > G and SNP+299G > A) gene polymorphisms in the genetic risk underlying type 2 diabetes (T2DM) and metabolic syndrome (MS) were assessed. The potential mutual influence of the ADIPOQ and RETN genes on their adipokine levels was also examined. The rare homozygous genotype (risk alleles) of SNP-420C > G at the RETN locus tended to be co-inherited together with the common homozygous genotypes (protective alleles) of SNP+639T > C and SNP+1212A > G at the ADIPOQ locus. Despite the close structural relationship between the ADIPOQ and RETN genes, there was no evidence of an intermolecular epistatic interaction between these genes. There was also no reciprocal effect of the ADIPOQ and RETN genes on their adipokine levels, i.e., ADIPOQ did not affect resistin levels nor did RETN affect adiponectin levels. The possible influence of the ADIPOQ gene on RETN expression warrants further investigation.
Recently, the greatest statistical computational challenge in genetic epidemiology is to identify and characterize the genes that interact with other genes and environment factors that bring the effect on complex multifactorial disease. These gene-gene interactions are also denoted as epitasis in which this phenomenon cannot be solved by traditional statistical method due to the high dimensionality of the data and the occurrence of multiple polymorphism. Hence, there are several machine learning methods to solve such problems by identifying such susceptibility gene which are neural networks (NNs), support vector machine (SVM), and random forests (RFs) in such common and multifactorial disease. This paper gives an overview on machine learning methods, describing the methodology of each machine learning methods and its application in detecting gene-gene and gene-environment interactions. Lastly, this paper discussed each machine learning method and presents the strengths and weaknesses of each machine learning method in detecting gene-gene interactions in complex human disease.
High kernel elongation (HKE) is one of the high-quality characteristics in rice. The objectives of this study were to determine the effects of ageing treatments, gene actions, and inheritance pattern of kernel elongation on cooking quality in two populations of rice and determine the path of influence and contribution of other traits to kernel elongation in rice. Two rice populations derived from crosses between MR219 × Mahsuri Mutan and MR219 × Basmati 370 were used. The breeding materials included two F1 progenies from the two populations, and their respective parents were grown in four different batches at a week interval to synchronize the flowering between the female and male plants. Scaling tests and generation means analysis were carried out to determine ageing effects and estimate additive-dominance gene action and epistasis. The estimation of gene interaction was based on quantitative traits. Path coefficient analysis was done using SAS software version 9.4 to determine the path of influence (direct or indirect) of six quantitative traits on HKE. Results obtained showed that nonallelic gene interaction was observed in all traits. The results before ageing and after ageing showed significant differences in all traits, while the gene interaction changed after ageing. The HKE value improved after ageing, suggesting that ageing is an external factor that could influence gene expression. The epistasis effect for HKE obtained from the cross Mahsuri Mutan × MR219 showed duplicate epistasis while that obtained from a cross between Basmati 370 × MR219 showed complimentary epistasis. Besides, the heritability of HKE was higher in Basmati 370 × MR219 compared to that obtained in Mahsuri Mutan × MR219. The path analysis showed that the cooked grain length and length-width ratio positively significantly affected HKE. It was concluded that ageing treatment is an external factor that could improve the expression of HKE. The findings from this study would be useful to breeders in the selection and development of new specialty (HKE) rice varieties.
The Apolipoprotein E ε4 (APOE ε4) haplotype is the strongest genetic risk factor for late-onset Alzheimer's disease (AD). The Translocase of Outer Mitochondrial Membrane-40 (TOMM40) gene maintains cellular bioenergetics, which is disrupted in AD. TOMM40 rs2075650 ('650) G versus A carriage is consistently related to neural and cognitive outcomes, but it is unclear if and how it interacts with APOE. We examined 21 orthogonal neural networks among 8,222 middle-aged to aged participants in the UK Biobank cohort. ANOVA and multiple linear regression tested main effects and interactions with APOE and TOMM40 '650 genotypes, and if age and sex acted as moderators. APOE ε4 was associated with less strength in multiple networks, while '650 G versus A carriage was related to more language comprehension network strength. In APOE ε4 carriers, '650 G-carriage led to less network strength with increasing age, while in non-G-carriers this was only seen in women but not men. TOMM40 may shift what happens to network activity in aging APOE ε4 carriers depending on sex.
The incidence and mortality of breast cancer continues to rise rapidly in Asian countries. However, most of our current knowledge on breast cancer has been generated in Western populations. As the socio-economic profile, life style and culture of Asian and Western women are substantially different, and genetic backgrounds vary to some extent, we need to answer the question on whether to 'adopt' or 'adapt' Western knowledge before applying it in the Asian setting. It is generally accepted that breast cancer risk factors, which have mainly been studied in Western populations are similar worldwide. However, the presence of gene-environment or gene-gene interactions may alter their importance as causal factors across populations. Diagnostic and prognostic study findings, including breast cancer prediction rules, are increasingly shown to be 'setting specific' and must therefore be validated in Asian women before implementing them in clinical care in Asia. Interventional research findings from Caucasian patients may not be applicable in patients in Asia due to differences in tumour biology/profiles, metabolism of drugs and also health beliefs which can influence treatment acceptance and adherence. While breast cancer research in Asia is warranted in all domains of medical research, it is felt that for Asian breast cancer patients, needs are highest for diagnostic and prognostic studies. International clinical trials meanwhile need to include breast cancer patients from various Asian settings to provide an insight into the effectiveness of new treatment modalities in this part of the world.
Irregular atrial pressure, defective folate and cholesterol metabolism contribute to the pathogenesis of hypertension. However, little is known about the combined roles of the methylenetetrahydrofolate reductase (MTHFR), apolipoprotein-E (ApoE) and angiotensin-converting enzyme (ACE) genes, which are involved in metabolism and homeostasis. The objective of this study is to investigate the association of the MTHFR 677 C>T and 1298A>C, ACE insertion-deletion (I/D) and ApoE genetic polymorphisms with hypertension and to further explore the epistasis interactions that are involved in these mechanisms. A total of 594 subjects, including 348 normotensive and 246 hypertensive ischemic stroke subjects were recruited. The MTHFR 677 C>T and 1298A>C, ACE I/D and ApoEpolymorphisms were genotyped and the epistasis interaction were analyzed. The MTHFR 677 C>T and ApoE polymorphisms demonstrated significant associations with susceptibility to hypertension in multiple logistic regression models, multifactor dimensionality reduction and a classification and regression tree. In addition, the logistic regression model demonstrated that significant interactions between the ApoE E3E3, E2E4, E2E2 and MTHFR 677 C>T polymorphisms existed. In conclusion, the results of this epistasis study indicated significant association between the ApoE and MTHFR polymorphisms and hypertension.
Genetic polymorphism has been implicated as a factor for the occurrence of non-alcoholic fatty liver disease (NAFLD). This study attempted to assess whether polymorphisms in the leptin receptor (LEPR) gene and its combined effect with patatin-like phospholipase domain-containing protein 3 (PNPLA3/adiponutrin) are associated with risk of NAFLD.
RAR-related orphan receptors A (RORA) and B (RORB) and voltage-gated sodium channel type 1 (SCN1A) genes play critical roles in the regulation of the circadian clock. Evidence has shown an association of RORA and RORB polymorphisms with susceptibility to autism and depression. Hence, we tested the association of RORA rs12912233, rs16943429, rs880626, rs2290430, and rs12900948; RORB rs1157358, rs7022435, rs3750420, and rs3903529; and SCN1A rs3812718 with epilepsy risk in the Malaysians. DNA was genotyped in 1789 subjects (39% epilepsy patients) by using MassARRAY (Sequenom). Significant association was obtained for rs12912233 in Malaysian Chinese (p=0.003). Interaction between rs12912233-rs880626 and rs3812718 was associated with the epilepsy risk in the subjects overall (p=0.001). Results show that RORA rs12912233 alone might be a possible risk variant for epilepsy in Malaysian Chinese, but that, together with RORA rs880626 and SCN1A rs3812718, this polymorphism may have a synergistic effect in the epilepsy risk in Malaysians.
Angiotensin II type 1 receptor (AGTR1) has been reported to play a fibrogenic role in non-alcoholic fatty liver disease (NAFLD). In this study, five variants of the AGTR1 gene (rs3772622, rs3772627, rs3772630, rs3772633, and rs2276736) were examined for their association with susceptibility to NAFLD. Subjects made up of 144 biopsy-proven NAFLD patients and 198 controls were genotyped using TaqMan assays. The liver biopsy specimens were histologically graded and scored according to the method of Brunt. Single locus analysis in pooled subjects revealed no association between each of the five variants with susceptibility to NAFLD. In the Indian ethnic group, the rs2276736, rs3772630 and rs3772627 appear to be protective against NAFLD (p = 0.010, p = 0.016 and p = 0.026, respectively). Haplotype ACGCA is shown to be protective against NAFLD for the Indian ethnic subgroup (p = 0.03). Gene-gene interaction between the AGTR1 gene and the patatin-like phospholipase domain-containing 3 (PNPLA3) gene, which we previously reported as associated with NAFLD in this sample, showed a strong interaction between AGTR1 (rs3772627), AGTRI (rs3772630) and PNPLA3 (rs738409) polymorphisms on NAFLD susceptibility (p = 0.007). Further analysis of the NAFLD patients revealed that the G allele of the AGTR1 rs3772622 is associated with increased fibrosis score (p = 0.003). This is the first study that replicates an association between AGTR1 polymorphism and NAFLD, with further details in histological features of NAFLD. There is lack of evidence to suggest an association between any of the five variants of the AGTR1 gene and NAFLD in the Malays and Chinese. In the Indians, the rs2276736, rs3772630 and rs3772627 appear to protect against NAFLD. We report novel findings of an association between the G allele of the rs3772622 with occurrence of fibrosis and of the gene-gene interaction between AGTR1gene and the much-studied PNPLA3 gene.
Diabetes mellitus (DM) is a major health problem worldwide and it will rapidly increase. This disease is characterized by hyperglycemia caused by defects in insulin secretion, insulin action or both. DM has three types: T1DM, T2M and gestational DM (GDM), of them T2DM is more frequent. Multiple genes and their interactions are involved in insulin secretion pathway. Sulfonylurea receptor encoded by ABCC8 gene, together with inward-rectifier potassium ion channel (Kir6.2) regulates insulin secretion by ATP-sensitive K(+) (KATP) channel located in the plasma membranes. Disruption of these molecules by different mutations is responsible for risk of DM. Several single nucleotide polymorphisms (SNPs) of ABCC8 gene and their interaction are involved in pathogenicity of DM. This review summarizes the current evidence of contribution of ABC8 genetic variants to the development of DM.
Malaysian rice, Pongsu Seribu 2, has wide-spectrum resistance against blast disease. Chromosomal locations conferring quantitative resistance were detected by linkage mapping with SSRs and quantitative trait locus (QTL) analysis. For the mapping population, 188 F3 families were derived from a cross between the susceptible cultivar, Mahsuri, and a resistant variety, Pongsu Seribu 2. Partial resistance to leaf blast in the mapping population was assessed. A linkage map covering ten chromosomes and consisting of 63 SSR markers was constructed. 13 QTLs, including 6 putative and 7 putative QTLs, were detected on chromosomes 1, 2, 3, 5, 6, 10, 11 and 12. The resulting phenotypic variation due to a single QTL ranged from 2 to 13 %. These QTLs accounted for approx. 80 % of the total phenotypic variation within the F3 population. Therefore, partial resistance to blast in Pongsu Seribu 2 is due to combined effects of multiple loci with major and minor effects.