A genome-wide screen for interactions reveals a new locus on 4p15 modifying the effect of waist-to-hip ratio on total cholesterol

Quantile-specific heritability of total cholesterol and its pharmacogenetic and nutrigenetic implications

BACKGROUND

"Quantile-dependent expressivity" occurs when the effect size of a genetic variant depends upon whether the phenotype (e.g. cholesterol) is high or low relative to its distribution. We have previously shown that the effect of a 52-SNP genetic-risk score was 3-fold larger at the 90th percentile of the total cholesterol distribution than at its 10th percentile. The objective of this study is to assess quantile-dependent expressivity for total cholesterol in 7006 offspring with parents and 2112 sibships from Framingham Heart Study.

METHODS

Quantile-specific heritability (h²) was estimated as twice the offspring-parent regression slope as robustly estimated by quantile regression with nonparametric significance assigned from 1000 bootstrap samples.

RESULTS

Quantile-specific h² increased linearly with increasing percentiles of the offspring's cholesterol distribution (P = 3.0 × 10^-9), i.e. h² = 0.38 at the 10th percentile, h² = 0.45 at the 25th percentile, h² = 0.52 at the 50th, h² = 0.61 at the 75th percentile, and h² = 0.65 at the 90th percentile of the total cholesterol distribution. Average h² decreased from 0.55 to 0.34 in 3564 offspring who started cholesterol-lowering medications, but this was attributable to quantile-dependent expressivity and the offspring's 0.94 mmol/L average drop in total cholesterol. Quantile-dependent expressivity likely explains the reported effect of the CELSR2/PSRC1/SORT1 rs646776 and APOE rs7412 gene loci on statin efficacy. Specifically, a smaller genetic effect size at the lower (post-treatment) than higher (pre-treatment) cholesterol concentrations mandates that the trajectories of the genotypes cannot move in parallel when cholesterol is decreased pharmacologically.

CONCLUSION

Cholesterol concentrations exhibit quantile-dependent expressivity, which may provide an alternative interpretation to pharmacogenetic and nutrigenetic interactions.

A genome-wide search for gene-by-obesity interaction loci of dyslipidemia in Koreans shows diverse genetic risk alleles

Dyslipidemia is a well-established risk factor for CVD. Studies suggest that similar fat accumulation in a given population might result in different levels of dyslipidemia risk among individuals; for example, despite similar or leaner body composition compared with Caucasians, Asians of Korean descent experience a higher prevalence of dyslipidemia. These variations imply a possible role of gene-obesity interactions on lipid profiles. Genome-wide association studies have identified more than 500 loci regulating plasma lipids, but the interaction structure between genes and obesity traits remains unclear. We hypothesized that some loci modify the effects of obesity on dyslipidemia risk and analyzed extensive gene-environment interactions (G×Es) at genome-wide levels to search for replicated gene-obesity interactive SNPs. In four Korean cohorts (n = 18,025), we identified and replicated 20 gene-obesity interactions, including novel variants (SCN1A and SLC12A8) and known lipid-associated variants (APOA5, BUD13, ZNF259, and HMGCR). When we estimated the additional heritability of dyslipidemia by considering G×Es, the gain was substantial for triglycerides (TGs) but mild for LDL cholesterol (LDL-C) and total cholesterol (Total-C); the interaction explained up to 18.7% of TG, 2.4% of LDL-C, and 1.9% of Total-C heritability associated with waist-hip ratio. Our findings suggest that some individuals are prone to develop abnormal lipid profiles, particularly with regard to TGs, even with slight increases in obesity indices; ethnic diversities in the risk alleles might partly explain the differential dyslipidemia risk between populations. Research about these interacting variables may facilitate knowledge-based approaches to personalize health guidelines according to individual genetic profiles.

Adult onset asthma and interaction between genes and active tobacco smoking: The GABRIEL consortium

Background

Genome-wide association studies have identified novel genetic associations for asthma, but without taking into account the role of active tobacco smoking. This study aimed to identify novel genes that interact with ever active tobacco smoking in adult onset asthma.

Methods

We performed a genome-wide interaction analysis in six studies participating in the GABRIEL consortium following two meta-analyses approaches based on 1) the overall interaction effect and 2) the genetic effect in subjects with and without smoking exposure. We performed a discovery meta-analysis including 4,057 subjects of European descent and replicated our findings in an independent cohort (LifeLines Cohort Study), including 12,475 subjects.

Results

First approach: 50 SNPs were selected based on an overall interaction effect at p<10⁻⁴. The most pronounced interaction effect was observed for rs9969775 on chromosome 9 (discovery meta-analysis: OR_int = 0.50, p = 7.63*10⁻⁵, replication: OR_int = 0.65, p = 0.02). Second approach: 35 SNPs were selected based on the overall genetic effect in exposed subjects (p <10⁻⁴). The most pronounced genetic effect was observed for rs5011804 on chromosome 12 (discovery meta-analysis OR_int = 1.50, p = 1.21*10^−4; replication: OR_int = 1.40, p = 0.03).

Conclusions

Using two genome-wide interaction approaches, we identified novel polymorphisms in non-annotated intergenic regions on chromosomes 9 and 12, that showed suggestive evidence for interaction with active tobacco smoking in the onset of adult asthma.

Genome-Wide Meta-Analysis of Sciatica in Finnish Population

Sciatica or the sciatic syndrome is a common and often disabling low back disorder in the working-age population. It has a relatively high heritability but poorly understood molecular mechanisms. The Finnish population is a genetic isolate where small founder population and bottleneck events have led to enrichment of certain rare and low frequency variants. We performed here the first genome-wide association (GWAS) and meta-analysis of sciatica. The meta-analysis was conducted across two GWAS covering 291 Finnish sciatica cases and 3671 controls genotyped and imputed at 7.7 million autosomal variants. The most promising loci (p<1x10^-6) were replicated in 776 Finnish sciatica patients and 18,489 controls. We identified five intragenic variants, with relatively low frequencies, at two novel loci associated with sciatica at genome-wide significance. These included chr9:14344410:I (rs71321981) at 9p22.3 (NFIB gene; p = 1.30x10^-8, MAF = 0.08) and four variants at 15q21.2: rs145901849, rs80035109, rs190200374 and rs117458827 (MYO5A; p = 1.34x10^-8, MAF = 0.06; p = 2.32x10^-8, MAF = 0.07; p = 3.85x10^-8, MAF = 0.06; p = 4.78x10^-8, MAF = 0.07, respectively). The most significant association in the meta-analysis, a single base insertion rs71321981 within the regulatory region of the transcription factor NFIB, replicated in an independent Finnish population sample (p = 0.04). Despite identifying 15q21.2 as a promising locus, we were not able to replicate it. It was differentiated; the lead variants within 15q21.2 were more frequent in Finland (6–7%) than in other European populations (1–2%). Imputation accuracies of the three significantly associated variants (chr9:14344410:I, rs190200374, and rs80035109) were validated by genotyping. In summary, our results suggest a novel locus, 9p22.3 (NFIB), which may be involved in susceptibility to sciatica. In addition, another locus, 15q21.2, emerged as a promising one, but failed to replicate.

Putting the Genome in Context: Gene-Environment Interactions in Type 2 Diabetes

The genome is often the conduit through which environmental exposures convey their effects on health and disease. Whilst not all diseases act by directly perturbing the genome, the phenotypic responses are often genetically determined. Hence, whilst diseases are often defined has having differing degrees of genetic determination, genetic and environmental factors are, with few exceptions, inseparable features of most diseases, not least type 2 diabetes. It follows that to optimize diabetes, prevention and treatment will require that the etiological roles of genetic and environmental risk factors be jointly considered. As we discuss here, studies focused on quantifying gene-environment and gene-treatment interactions are gathering momentum and may eventually yield data that helps guide health-related choices and medical interventions for type 2 diabetes and other complex diseases.

Variants for HDL-C, LDL-C, and triglycerides identified from admixture mapping and fine-mapping analysis in African American families

BACKGROUND

Admixture mapping of lipids was followed-up by family-based association analysis to identify variants for cardiovascular disease in African Americans.

METHODS AND RESULTS

The present study conducted admixture mapping analysis for total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides. The analysis was performed in 1905 unrelated African American subjects from the National Heart, Lung and Blood Institute's Family Blood Pressure Program (FBPP). Regions showing admixture evidence were followed-up with family-based association analysis in 3556 African American subjects from the FBPP. The admixture mapping and family-based association analyses were adjusted for age, age(2), sex, body mass index, and genome-wide mean ancestry to minimize the confounding caused by population stratification. Regions that were suggestive of local ancestry association evidence were found on chromosomes 7 (low-density lipoprotein cholesterol), 8 (high-density lipoprotein cholesterol), 14 (triglycerides), and 19 (total cholesterol and triglycerides). In the fine-mapping analysis, 52 939 single-nucleotide polymorphisms (SNPs) were tested and 11 SNPs (8 independent SNPs) showed nominal significant association with high-density lipoprotein cholesterol (2 SNPs), low-density lipoprotein cholesterol (4 SNPs), and triglycerides (5 SNPs). The family data were used in the fine-mapping to identify SNPs that showed novel associations with lipids and regions, including genes with known associations for cardiovascular disease.

CONCLUSIONS

This study identified regions on chromosomes 7, 8, 14, and 19 and 11 SNPs from the fine-mapping analysis that were associated with high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides for further studies of cardiovascular disease in African Americans.

The challenges of genome-wide interaction studies: lessons to learn from the analysis of HDL blood levels

Genome-wide association studies (GWAS) have revealed 74 single nucleotide polymorphisms (SNPs) associated with high-density lipoprotein cholesterol (HDL) blood levels. This study is, to our knowledge, the first genome-wide interaction study (GWIS) to identify SNP×SNP interactions associated with HDL levels. We performed a GWIS in the Rotterdam Study (RS) cohort I (RS-I) using the GLIDE tool which leverages the massively parallel computing power of Graphics Processing Units (GPUs) to perform linear regression on all genome-wide pairs of SNPs. By performing a meta-analysis together with Rotterdam Study cohorts II and III (RS-II and RS-III), we were able to filter 181 interaction terms with a p-value<1 · 10⁻⁸ that replicated in the two independent cohorts. We were not able to replicate any of these interaction term in the AGES, ARIC, CHS, ERF, FHS and NFBC-66 cohorts (N_total = 30,011) when adjusting for multiple testing. Our GWIS resulted in the consistent finding of a possible interaction between rs774801 in ARMC8 (ENSG00000114098) and rs12442098 in SPATA8 (ENSG00000185594) being associated with HDL levels. However, p-values do not reach the preset Bonferroni correction of the p-values. Our study suggest that even for highly genetically determined traits such as HDL the sample sizes needed to detect SNP×SNP interactions are large and the 2-step filtering approaches do not yield a solution. Here we present our analysis plan and our reservations concerning GWIS.

Effect of genetic and non-genetic factors, including aging, on waist circumference and BMI, and inter-indicator differences in risk assessment

OBJECTIVE

To assess the effect of genetic and non-genetic factors on indicators derived from waist circumference (WC) and body mass index (BMI) as well as inter-indicator differences in risk assessment age-related diseases including diabetes mellitus, coronary heart disease and liver cancer.

METHODS

Height, weight and WC were measured in 100 families (students and their two parents), 41 subjects with regular physical exercise routines, and 170 patients with diabetes mellitus, coronary heart disease or liver cancer. The BMI, waist-height ratio (WHtR) and waist circumference density index (WCDI) were calculated for each subject.

RESULTS

BMI was less affected by genetic factors, while WHtR and WCDI were greatly affected by genetic factors as revealed using multiple regression analysis. BMI, WHtR and WCDI were all sensitive to physical exercise according to ROC analysis; among these factors, the most sensitive indicator was WHtR. However, ROC analysis demonstrated that WCDI was more effective than BMI and WHtR for assessing the risk of three diseases.

CONCLUSIONS

WCDI more accurately reflects the roles of both genetic and non-genetic factors, including aging, which can better predict disease.

Gene-age interactions in blood pressure regulation: a large-scale investigation with the CHARGE, Global BPgen, and ICBP Consortia

Although age-dependent effects on blood pressure (BP) have been reported, they have not been systematically investigated in large-scale genome-wide association studies (GWASs). We leveraged the infrastructure of three well-established consortia (CHARGE, GBPgen, and ICBP) and a nonstandard approach (age stratification and metaregression) to conduct a genome-wide search of common variants with age-dependent effects on systolic (SBP), diastolic (DBP), mean arterial (MAP), and pulse (PP) pressure. In a two-staged design using 99,241 individuals of European ancestry, we identified 20 genome-wide significant (p ≤ 5 × 10(-8)) loci by using joint tests of the SNP main effect and SNP-age interaction. Nine of the significant loci demonstrated nominal evidence of age-dependent effects on BP by tests of the interactions alone. Index SNPs in the EHBP1L1 (DBP and MAP), CASZ1 (SBP and MAP), and GOSR2 (PP) loci exhibited the largest age interactions, with opposite directions of effect in the young versus the old. The changes in the genetic effects over time were small but nonnegligible (up to 1.58 mm Hg over 60 years). The EHBP1L1 locus was discovered through gene-age interactions only in whites but had DBP main effects replicated (p = 8.3 × 10(-4)) in 8,682 Asians from Singapore, indicating potential interethnic heterogeneity. A secondary analysis revealed 22 loci with evidence of age-specific effects (e.g., only in 20 to 29-year-olds). Age can be used to select samples with larger genetic effect sizes and more homogenous phenotypes, which may increase statistical power. Age-dependent effects identified through novel statistical approaches can provide insight into the biology and temporal regulation underlying BP associations.

Genetic risk score and adiposity interact to influence triglyceride levels in a cohort of Filipino women

Background/Objectives:

Individually, genetic variants only moderately influence cardiometabolic (CM) traits, such as lipid and inflammatory markers. In this study we generated genetic risk scores from a combination of previously reported variants influencing CM traits, and used these scores to explore how adiposity levels could mediate genetic contributions to CM traits.

Subjects/Methods:

Participants included 1649 women from the 2005 Cebu Longitudinal Health and Nutrition Survey. Three genetic risk scores were constructed for C-reactive protein (CRP), high-density lipoprotein cholesterol (HDL-C) and triglycerides (TGs). We used linear regression models to assess the association between each genetic risk score and its related trait. We also tested for interactions between each score and measures of adiposity.

Results:

Each genetic risk score explained a greater proportion of variance in trait levels than any individual genetic variant. We found an interaction between the TG genetic risk score (2.29–14.34 risk alleles) and waist circumference (WC) (P_interaction=1.66 × 10⁻²). Based on model predictions, for individuals with a higher TG genetic risk score (75th percentile=12), having an elevated WC (⩾80 cm) increased TG levels from 1.32 to 1.71 mmol l⁻¹. However, for individuals with a lower score (25th percentile=7), having an elevated WC did not significantly change TG levels.

Conclusions:

The TG genetic risk score interacted with adiposity to synergistically influence TG levels. For individuals with a genetic predisposition to elevated TG levels, our results suggest that reducing adiposity could possibly prevent further increases in TG levels and thereby lessen the likelihood of adverse health outcomes such as cardiovascular disease.

Quality control and conduct of genome-wide association meta-analyses

Rigorous organization and quality control (QC) are necessary to facilitate successful genome-wide association meta-analyses (GWAMAs) of statistics aggregated across multiple genome-wide association studies. This protocol provides guidelines for (i) organizational aspects of GWAMAs, and for (ii) QC at the study file level, the meta-level across studies and the meta-analysis output level. Real-world examples highlight issues experienced and solutions developed by the GIANT Consortium that has conducted meta-analyses including data from 125 studies comprising more than 330,000 individuals. We provide a general protocol for conducting GWAMAs and carrying out QC to minimize errors and to guarantee maximum use of the data. We also include details for the use of a powerful and flexible software package called EasyQC. Precise timings will be greatly influenced by consortium size. For consortia of comparable size to the GIANT Consortium, this protocol takes a minimum of about 10 months to complete.

Additive influence of genetic predisposition and conventional risk factors in the incidence of coronary heart disease: a population-based study in Greece

OBJECTIVES

An additive genetic risk score (GRS) for coronary heart disease (CHD) has previously been associated with incident CHD in the population-based Greek European Prospective Investigation into Cancer and nutrition (EPIC) cohort. In this study, we explore GRS-'environment' joint actions on CHD for several conventional cardiovascular risk factors (ConvRFs), including smoking, hypertension, type-2 diabetes mellitus (T2DM), body mass index (BMI), physical activity and adherence to the Mediterranean diet.

DESIGN

A case-control study.

SETTING

The general Greek population of the EPIC study.

PARTICIPANTS AND OUTCOME MEASURES

477 patients with medically confirmed incident CHD and 1271 controls participated in this study. We estimated the ORs for CHD by dividing participants at higher or lower GRS and, alternatively, at higher or lower ConvRF, and calculated the relative excess risk due to interaction (RERI) as a measure of deviation from additivity.

RESULTS

The joint presence of higher GRS and higher risk ConvRF was in all instances associated with an increased risk of CHD, compared with the joint presence of lower GRS and lower risk ConvRF. The OR (95% CI) was 1.7 (1.2 to 2.4) for smoking, 2.7 (1.9 to 3.8) for hypertension, 4.1 (2.8 to 6.1) for T2DM, 1.9 (1.4 to 2.5) for lower physical activity, 2.0 (1.3 to 3.2) for high BMI and 1.5 (1.1 to 2.1) for poor adherence to the Mediterranean diet. In all instances, RERI values were fairly small and not statistically significant, suggesting that the GRS and the ConvRFs do not have effects beyond additivity.

CONCLUSIONS

Genetic predisposition to CHD, operationalised through a multilocus GRS, and ConvRFs have essentially additive effects on CHD risk.

Genetic insights into cardiometabolic risk factors

Many biochemical traits are recognised as risk factors, which contribute to or predict the development of disease. Only a few are in widespread use, usually to assist with treatment decisions and motivate behavioural change. The greatest effort has gone into evaluation of risk factors for cardiovascular disease and/or diabetes, with substantial overlap as 'cardiometabolic' risk. Over the past few years many genome-wide association studies (GWAS) have sought to account for variation in risk factors, with the expectation that identifying relevant polymorphisms would improve our understanding or prediction of disease; others have taken the direct approach of genomic case-control studies for the corresponding diseases. Large GWAS have been published for coronary heart disease and Type 2 diabetes, and also for associated biomarkers or risk factors including body mass index, lipids, C-reactive protein, urate, liver function tests, glucose and insulin. Results are not encouraging for personal risk prediction based on genotyping, mainly because known risk loci only account for a small proportion of risk. Overlap of allelic associations between disease and marker, as found for low density lipoprotein cholesterol and heart disease, supports a causal association, but in other cases genetic studies have cast doubt on accepted risk factors. Some loci show unexpected effects on multiple markers or diseases. An intriguing feature of risk factors is the blurring of categories shown by the correlation between them and the genetic overlap between diseases previously thought of as distinct. GWAS can provide insight into relationships between risk factors, biomarkers and diseases, with potential for new approaches to disease classification.

Genetic association with lipids in Filipinos: waist circumference modifies an APOA5 effect on triglyceride levels

Blood levels of lipoprotein cholesterol and triglycerides (TGs) are highly heritable and are major risk factors for cardiovascular disease (CVD). Approximately 100 lipid-associated loci have been identified in populations of European ancestry. We performed a genome-wide association study of lipid traits in 1,782 Filipino women from the Cebu Longitudinal Health and Nutrition Survey, and tested for evidence of interactions with waist circumference. We conducted additional association and interaction analyses in 1,719 of their young adult offspring. Genome-wide significant associations (P < 5 × 10⁻⁸) were detected at APOE for low density lipoprotein cholesterol and total cholesterol, and at APOA5 for TGs. Suggestive associations (P < 10⁻⁶) were detected at GCKR for TGs, and at CETP and TOM1 for high density lipoprotein cholesterol. Our data also supported the existence of allelic heterogeneity at APOA5, CETP, LIPC, and APOE. The secondary signal (Gly185Cys) at APOA5 exhibited a single nucleotide polymorphism (SNP)-by-waist circumference interaction affecting TGs (Pinteraction = 1.6 × 10⁻⁴), manifested by stronger SNP effects as waist circumference increased. These findings provide the first evidence that central obesity may accentuate the effect of the TG-increasing allele of the APOA5 signal, emphasizing that CVD risk could be reduced by central obesity control.

Prenatal diagnosis and molecular cytogenetic characterization of a de novo proximal interstitial deletion of chromosome 4p (4p15.2→p14)

We present prenatal diagnosis of de novo proximal interstitial deletion of chromosome 4p (4p15.2→p14) and molecular cytogenetic characterization of the deletion using uncultured amniocytes. We review the phenotypic abnormalities of previously reported patients with similar proximal interstitial 4p deletions, and we discuss the functions of the genes of RBPJ, CCKAR, STIM2, PCDH7 and ARAP2 that are deleted within this region.

Genomic, Transcriptomic, and Lipidomic Profiling Highlights the Role of Inflammation in Individuals With Low High-density Lipoprotein Cholesterol

Objective—

Low high-density lipoprotein cholesterol (HDL-C) is associated with cardiometabolic pathologies. In this study, we investigate the biological pathways and individual genes behind low HDL-C by integrating results from 3 high-throughput data sources: adipose tissue transcriptomics, HDL lipidomics, and dense marker genotypes from Finnish individuals with low or high HDL-C (n=450).

Approach and Results—

In the pathway analysis of genetic data, we demonstrate that genetic variants within inflammatory pathways were enriched among low HDL-C associated single-nucleotide polymorphisms, and the expression of these pathways upregulated in the adipose tissue of low HDL-C subjects. The lipidomic analysis highlighted the change in HDL particle quality toward putatively more inflammatory and less vasoprotective state in subjects with low HDL-C, as evidenced by their decreased antioxidative plasmalogen contents. We show that the focal point of these inflammatory pathways seems to be the HLA region with its low HDL-associated alleles also associating with more abundant local transcript levels in adipose tissue, increased plasma vascular cell adhesion molecule 1 (VCAM1) levels, and decreased HDL particle plasmalogen contents, markers of adipose tissue inflammation, vascular inflammation, and HDL antioxidative potential, respectively. In a population-based look-up of the inflammatory pathway single-nucleotide polymorphisms in a large Finnish cohorts (n=11 211), no association of the HLA region was detected for HDL-C as quantitative trait, but with extreme HDL-C phenotypes, implying the presence of low or high HDL genes in addition to the population-genomewide association studies–identified HDL genes.

Conclusions—

Our study highlights the role of inflammation with a genetic component in subjects with low HDL-C and identifies novel cis -expression quantitative trait loci ( cis -eQTL) variants in HLA region to be associated with low HDL-C.

A genome-wide association study of monozygotic twin-pairs suggests a locus related to variability of serum high-density lipoprotein cholesterol

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 x 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-ll (P= 4.03 x 1 o-8).

Integrated approaches to functionally characterize novel factors in lipoprotein metabolism

PURPOSE OF REVIEW

To discuss if and how the combined analysis of large-scale datasets from multiple independent sources benefits the mapping of novel genetic elements with relevance to lipoprotein metabolism and allows for conclusions on underlying molecular mechanisms.

RECENT FINDINGS

Genome-wide association studies (GWAS) have identified numerous genomic loci associated with plasma lipid levels and cardiovascular disease. Yet, despite being highly successful in mapping novel loci the GWAS approach falls short to systematically extract functional information from genomic data. With the aim to complement GWAS for a better insight into disease mechanisms and identification of the most promising targets for drug development, a number of high-throughput functional genomics strategies have now been applied. These include computational approaches, consideration of gene-gene and gene-environment interactions, as well as unbiased gene-expression analyses in relevant tissues. For a limited number of loci, mechanistic insight has been gained through in-vitro and in-vivo studies by knockdown and overexpression of candidate genes.

SUMMARY

The integration of GWAS data with existing functional genomics strategies has contributed to ascertain the relevance of a number of novel factors for lipoprotein biology and disease. However, technologies are warranted that provide a more systematic insight into the molecular function and pathogenic relevance of promising candidate genes.

Sex-specific association of rs16996148 SNP in the NCAN/CILP2/PBX4 and serum lipid levels in the Mulao and Han populations

BACKGROUND

The association of rs16996148 single nucleotide polymorphism (SNP) in NCAN/CILP2/PBX4 and serum lipid levels is inconsistent. Furthermore, little is known about the association of rs16996148 SNP and serum lipid levels in the Chinese population. We therefore aimed to detect the association of rs16996148 SNP and several environmental factors with serum lipid levels in the Guangxi Mulao and Han populations.

METHOD

A total of 712 subjects of Mulao nationality and 736 participants of Han nationality were randomly selected from our stratified randomized cluster samples. Genotyping of the rs16996148 SNP was performed by polymerase chain reaction and restriction fragment length polymorphism combined with gel electrophoresis, and then confirmed by direct sequencing.

RESULTS

The levels of apolipoprotein (Apo) B were higher in Mulao than in Han (P < 0.001). The frequencies of G and T alleles were 87.2% and 12.8% in Mulao, and 89.9% and 10.1% in Han (P <0.05); respectively. The frequencies of GG, GT and TT genotypes were 76.0%, 22.5% and 1.5% in Mulao, and 81.2%, 17.4% and 1.4% in Han (P <0.05); respectively. There were no significant differences in the genotypic and allelic frequencies between males and females in both ethnic groups. The levels of HDL-C, ApoAI, and the ratio of ApoAI to ApoB in Mulao were different between the GG and GT/TT genotypes in males but not in females (P < 0.01 for all), the subjects with GT/TT genotypes had higher serum levels of HDL-C, ApoAI, and the ratio of ApoAI to ApoB than the subjects with GG genotype. The levels of TC, TG, LDL-C, ApoAI, and ApoB in Han were different between the GG and GT/TT genotypes in males but not in females (P < 0.05-0.001), the T allele carriers had higher serum levels of TC, TG, LDL-C, ApoAI, and ApoB than the T allele noncarriers. The levels of HDL-C, ApoAI, and the ratio of ApoAI to ApoB in Mulao were correlated with the genotypes in males (P < 0.05-0.01) but not in females. The levels of TC, TG, HDL-C, LDL-C, ApoAI and ApoB in Han were associated with the genotypes in males (P < 0.05-0.001) but not in females. Serum lipid parameters were also correlated with several enviromental factors in both ethnic groups (P < 0.05-0.001).

CONCLUSIONS

The genotypic and allelic frequencies of rs16996148 SNP and the associations of the SNP and serum lipid levels are different in the Mulao and Han populations. Sex (male)-specific association of rs16996148 SNP in the NCAN/CILP2/PBX4 and serum lipid levels is also observed in the both ethnic groups.