Yingchang Lu

Loss-of-Function Mutations in APOC3, Triglycerides, and Coronary Disease

BACKGROUND Plasma triglyceride levels are heritable and are correlated with the risk of coronary heart disease. Sequencing of the protein-coding regions of the human genome (the exome) has the potential to identify rare mutations that have a large effect on phenotype. METHODS We sequenced the protein-coding regions of 18,666 genes in each of 3734 participants of European or African ancestry in the Exome Sequencing Project. We conducted tests to determine whether rare mutations in coding sequence, individually or in aggregate within a gene, were associated with plasma triglyceride levels. For mutations associated with triglyceride levels, we subsequently evaluated their association with the risk of coronary heart disease in 110,970 persons. RESULTS An aggregate of rare mutations in the gene encoding apolipoprotein C3 (APOC3) was associated with lower plasma triglyceride levels. Among the four mutations that drove this result, three were loss-of-function mutations: a nonsense mutation (R19X) and two splice-site mutations (IVS2+1G→A and IVS3+1G→T). The fourth was a missense mutation (A43T). Approximately 1 in 150 persons in the study was a heterozygous carrier of at least one of these four mutations. Triglyceride levels in the carriers were 39% lower than levels in noncarriers (P<1×10(-20)), and circulating levels of APOC3 in carriers were 46% lower than levels in noncarriers (P=8×10(-10)). The risk of coronary heart disease among 498 carriers of any rare APOC3 mutation was 40% lower than the risk among 110,472 noncarriers (odds ratio, 0.60; 95% confidence interval, 0.47 to 0.75; P=4×10(-6)). CONCLUSIONS Rare mutations that disrupt APOC3 function were associated with lower levels of plasma triglycerides and APOC3. Carriers of these mutations were found to have a reduced risk of coronary heart disease. (Funded by the National Heart, Lung, and Blood Institute and others.).

Dietary n−3 and n−6 polyunsaturated fatty acid intake interacts with FADS1 genetic variation to affect total and HDL-cholesterol concentrations in the Doetinchem Cohort Study

BACKGROUND The delta-5 and delta-6 desaturases, encoded by the FADS1 and FADS2 genes, are rate-limiting enzymes in polyunsaturated fatty acid (PUFA) biosynthesis. Single nucleotide polymorphisms in the FADS gene cluster region have been associated with both PUFA concentrations in plasma or erythrocyte membrane phospholipids and cholesterol concentrations in recent genome-wide association studies. OBJECTIVE We examined whether genetic variations in the FADS gene cluster region interact with dietary intakes of n-3 (omega-3) and n-6 (omega-6) PUFAs to affect plasma total, HDL-, and non-HDL-cholesterol concentrations. DESIGN Dietary intakes of n-3 and n-6 PUFAs, plasma concentrations of total and HDL cholesterol, and rs174546, rs482548, and rs174570 in the FADS gene cluster region were measured in 3575 subjects in the second survey of the Doetinchem Cohort Study. RESULTS Significant associations between rs174546 genotypes and total and non-HDL-cholesterol concentrations were observed in the group with a high intake of n-3 PUFAs (> or =0.51% of total energy; P = 0.006 and 0.047, respectively) but not in the low-intake group (P for interaction = 0.32 and 0.51, respectively). The C allele was associated with high total and non-HDL-cholesterol concentrations. Furthermore, the C allele was significantly associated with high HDL-cholesterol concentrations in the group with a high intake of n-6 PUFAs (> or =5.26% of total energy, P = 0.004) but not in the group with a low intake (P for interaction = 0.02). CONCLUSION Genetic variation in the FADS1 gene potentially interacts with dietary PUFA intakes to affect plasma cholesterol concentrations, which should be investigated further in other studies.

Meta-analysis identifies common and rare variants influencing blood pressure and overlapping with metabolic trait loci

Meta-analyses of association results for blood pressure using exome-centric single-variant and gene-based tests identified 31 new loci in a discovery stage among 146,562 individuals, with follow-up and meta-analysis in 180,726 additional individuals (total n = 327,288). These blood pressure–associated loci are enriched for known variants for cardiometabolic traits. Associations were also observed for the aggregation of rare and low-frequency missense variants in three genes, NPR1, DBH, and PTPMT1. In addition, blood pressure associations at 39 previously reported loci were confirmed. The identified variants implicate biological pathways related to cardiometabolic traits, vascular function, and development. Several new variants are inferred to have roles in transcription or as hubs in protein–protein interaction networks. Genetic risk scores constructed from the identified variants were strongly associated with coronary disease and myocardial infarction. This large collection of blood pressure–associated loci suggests new therapeutic strategies for hypertension, emphasizing a link with cardiometabolic risk.

Obesity genomics: assessing the transferability of susceptibility loci across diverse populations

The prevalence of obesity has nearly doubled worldwide over the past three decades, but substantial differences exist between nations. Although these differences are partly due to the degree of westernization, genetic factors also contribute. To date, little is known about whether the same genes contribute to obesity-susceptibility in populations of different ancestry. We review the transferability of obesity-susceptibility loci (identified by genome-wide association studies) using both single nucleotide polymorphism (SNP) and locus-wide comparisons. SNPs in FTO and near MC4R, obesity-susceptibility loci first identified in Europeans, replicate widely across other ancestries. SNP-to-SNP comparisons suggest that more than half of the 36 body mass index-associated loci are shared across European and East Asian ancestry populations, whereas locus-wide analyses suggest that the transferability might be even more extensive. Furthermore, by taking advantage of differences in haplotype structure, populations of different ancestries can help to narrow down loci, thereby pinpointing causal genes for functional follow-up. Larger-scale genetic association studies in ancestrally diverse populations will be needed for in-depth and locus-wide analyses aimed at determining, with greater confidence, the transferability of loci and allowing fine-mapping. Understanding similarities and differences in genetic susceptibility across populations of diverse ancestries might eventually contribute to a more targeted prevention and customized treatment of obesity.

Literature-based genetic risk scores for coronary heart disease: the Cardiovascular Registry Maastricht (CAREMA) prospective cohort study.

Background— Genome-wide association studies (GWAS) have identified many single-nucleotide polymorphisms (SNPs) associated with coronary heart disease (CHD) or CHD risk factors (RF). Using a case-cohort study within the prospective Cardiovascular Registry Maastricht (CAREMA) cohort, we tested if genetic risk scores (GRS) based on GWAS-identified SNPs are associated with and predictive for future CHD. Methods and Results— Incident cases (n=742), that is, participants who developed CHD during a median follow-up of 12.1 years (range, 0.0–16.9 years), were compared with a randomly selected subcohort of 2221 participants selected from the total cohort (n=21 148). We genotyped 179 SNPs previously associated with CHD or CHD RF in GWAS as published up to May 2, 2011. The allele-count GRS, composed of all SNPs, the 153 RF SNPs, or the 29 CHD SNPs were not associated with CHD independent of CHD RF. The weighted 29 CHD SNP GRS, with weights obtained from GWAS for every SNP, were associated with CHD independent of CHD RF (hazard ratio, 1.12 per weighted risk allele; 95% confidence interval, 1.04–1.21) and improved risk reclassification with 2.8% (P=0.031). As an exploratory approach to achieve weighting, we performed least absolute shrinkage and selection operator (LASSO) regression analysis on all SNPs and the CHD SNPs. The CHD LASSO GRS performed equal to the weighted CHD GRS, whereas the Overall LASSO GRS performed slightly better than the weighted CHD GRS. Conclusions— A GRS composed of CHD SNPs improves risk prediction when adjusted for the effect sizes of the SNPs. Alternatively LASSO regression analysis may be used to achieve weighting; however, validation in independent populations is required.Background— Genome-wide association studies (GWAS) have identified many single-nucleotide polymorphisms (SNPs) associated with coronary heart disease (CHD) or CHD risk factors (RF). Using a case-cohort study within the prospective Cardiovascular Registry Maastricht (CAREMA) cohort, we tested if genetic risk scores (GRS) based on GWAS-identified SNPs are associated with and predictive for future CHD. Methods and Results— Incident cases (n=742), that is, participants who developed CHD during a median follow-up of 12.1 years (range, 0.0–16.9 years), were compared with a randomly selected subcohort of 2221 participants selected from the total cohort (n=21 148). We genotyped 179 SNPs previously associated with CHD or CHD RF in GWAS as published up to May 2, 2011. The allele-count GRS, composed of all SNPs, the 153 RF SNPs, or the 29 CHD SNPs were not associated with CHD independent of CHD RF. The weighted 29 CHD SNP GRS, with weights obtained from GWAS for every SNP, were associated with CHD independent of CHD RF (hazard ratio, 1.12 per weighted risk allele; 95% confidence interval, 1.04–1.21) and improved risk reclassification with 2.8% ( P =0.031). As an exploratory approach to achieve weighting, we performed least absolute shrinkage and selection operator (LASSO) regression analysis on all SNPs and the CHD SNPs. The CHD LASSO GRS performed equal to the weighted CHD GRS, whereas the Overall LASSO GRS performed slightly better than the weighted CHD GRS. Conclusions— A GRS composed of CHD SNPs improves risk prediction when adjusted for the effect sizes of the SNPs. Alternatively LASSO regression analysis may be used to achieve weighting; however, validation in independent populations is required.

Single-Trait and Multi-Trait Genome-Wide Association Analyses Identify Novel Loci for Blood Pressure in African-Ancestry Populations

Hypertension is a leading cause of global disease, mortality, and disability. While individuals of African descent suffer a disproportionate burden of hypertension and its complications, they have been underrepresented in genetic studies. To identify novel susceptibility loci for blood pressure and hypertension in people of African ancestry, we performed both single and multiple-trait genome-wide association analyses. We analyzed 21 genome-wide association studies comprised of 31,968 individuals of African ancestry, and validated our results with additional 54,395 individuals from multi-ethnic studies. These analyses identified nine loci with eleven independent variants which reached genome-wide significance (P < 1.25×10−8) for either systolic and diastolic blood pressure, hypertension, or for combined traits. Single-trait analyses identified two loci (TARID/TCF21 and LLPH/TMBIM4) and multiple-trait analyses identified one novel locus (FRMD3) for blood pressure. At these three loci, as well as at GRP20/CDH17, associated variants had alleles common only in African-ancestry populations. Functional annotation showed enrichment for genes expressed in immune and kidney cells, as well as in heart and vascular cells/tissues. Experiments driven by these findings and using angiotensin-II induced hypertension in mice showed altered kidney mRNA expression of six genes, suggesting their potential role in hypertension. Our study provides new evidence for genes related to hypertension susceptibility, and the need to study African-ancestry populations in order to identify biologic factors contributing to hypertension.

Comparative transcriptomic and metabolomic analysis of fenofibrate and fish oil treatments in mice

Elevated circulating triglycerides, which are considered a risk factor for cardiovascular disease, can be targeted by treatment with fenofibrate or fish oil. To gain insight into underlying mechanisms, we carried out a comparative transcriptomics and metabolomics analysis of the effect of 2 wk treatment with fenofibrate and fish oil in mice. Plasma triglycerides were significantly decreased by fenofibrate (-49.1%) and fish oil (-21.8%), whereas plasma cholesterol was increased by fenofibrate (+29.9%) and decreased by fish oil (-32.8%). Levels of various phospholipid species were specifically decreased by fish oil, while levels of Krebs cycle intermediates were increased specifically by fenofibrate. Plasma levels of many amino acids were altered by fenofibrate and to a lesser extent by fish oil. Both fenofibrate and fish oil upregulated genes involved in fatty acid metabolism and downregulated genes involved in blood coagulation and fibrinolysis. Significant overlap in gene regulation by fenofibrate and fish oil was observed, reflecting their property as high or low affinity agonist for peroxisome proliferator-activated receptor-α, respectively. Fenofibrate specifically downregulated genes involved in complement cascade and inflammatory response. Fish oil specifically downregulated genes involved in cholesterol and fatty acid biosynthesis and upregulated genes involved in amino acid and arachidonic acid metabolism. Taken together, the data indicate that despite being similarly potent toward modulating plasma free fatty acids, cholesterol, and triglyceride levels, fish oil causes modest changes in gene expression likely via activation of multiple mechanistic pathways, whereas fenofibrate causes pronounced gene expression changes via a single pathway, reflecting the key difference between nutritional and pharmacological intervention.

Meta-analysis of lipid-traits in Hispanics identifies novel loci, population-specific effects, and tissue-specific enrichment of eQTLs.

We performed genome-wide meta-analysis of lipid traits on three samples of Mexican and Mexican American ancestry comprising 4,383 individuals, and followed up significant and highly suggestive associations in three additional Hispanic samples comprising 7,876 individuals. Genome-wide significant signals were observed in or near CELSR2, ZNF259/APOA5, KANK2/DOCK6 and NCAN/MAU2 for total cholesterol, LPL, ABCA1, ZNF259/APOA5, LIPC and CETP for HDL cholesterol, CELSR2, APOB and NCAN/MAU2 for LDL cholesterol, and GCKR, TRIB1, ZNF259/APOA5 and NCAN/MAU2 for triglycerides. Linkage disequilibrium and conditional analyses indicate that signals observed at ABCA1 and LIPC for HDL cholesterol and NCAN/MAU2 for triglycerides are independent of previously reported lead SNP associations. Analyses of lead SNPs from the European Global Lipids Genetics Consortium (GLGC) dataset in our Hispanic samples show remarkable concordance of direction of effects as well as strong correlation in effect sizes. A meta-analysis of the European GLGC and our Hispanic datasets identified five novel regions reaching genome-wide significance: two for total cholesterol (FN1 and SAMM50), two for HDL cholesterol (LOC100996634 and COPB1) and one for LDL cholesterol (LINC00324/CTC1/PFAS). The top meta-analysis signals were found to be enriched for SNPs associated with gene expression in a tissue-specific fashion, suggesting an enrichment of tissue-specific function in lipid-associated loci.

Genomewide meta-analysis identifies loci associated with IGF-I and IGFBP-3 levels with impact on age-related traits

The growth hormone/insulin‐like growth factor (IGF) axis can be manipulated in animal models to promote longevity, and IGF‐related proteins including IGF‐I and IGF‐binding protein‐3 (IGFBP‐3) have also been implicated in risk of human diseases including cardiovascular diseases, diabetes, and cancer. Through genomewide association study of up to 30 884 adults of European ancestry from 21 studies, we confirmed and extended the list of previously identified loci associated with circulating IGF‐I and IGFBP‐3 concentrations (IGF1, IGFBP3, GCKR, TNS3, GHSR, FOXO3, ASXL2, NUBP2/IGFALS, SORCS2, and CELSR2). Significant sex interactions, which were characterized by different genotype–phenotype associations between men and women, were found only for associations of IGFBP‐3 concentrations with SNPs at the loci IGFBP3 and SORCS2. Analyses of SNPs, gene expression, and protein levels suggested that interplay between IGFBP3 and genes within the NUBP2 locus (IGFALS and HAGH) may affect circulating IGF‐I and IGFBP‐3 concentrations. The IGF‐I‐decreasing allele of SNP rs934073, which is an eQTL of ASXL2, was associated with lower adiposity and higher likelihood of survival beyond 90 years. The known longevity‐associated variant rs2153960 (FOXO3) was observed to be a genomewide significant SNP for IGF‐I concentrations. Bioinformatics analysis suggested enrichment of putative regulatory elements among these IGF‐I‐ and IGFBP‐3‐associated loci, particularly of rs646776 at CELSR2. In conclusion, this study identified several loci associated with circulating IGF‐I and IGFBP‐3 concentrations and provides clues to the potential role of the IGF axis in mediating effects of known (FOXO3) and novel (ASXL2) longevity‐associated loci.

No Association of Coronary Artery Disease with X-Chromosomal Variants in Comprehensive International Meta-Analysis.

In recent years, genome-wide association studies have identified 58 independent risk loci for coronary artery disease (CAD) on the autosome. However, due to the sex-specific data structure of the X chromosome, it has been excluded from most of these analyses. While females have 2 copies of chromosome X, males have only one. Also, one of the female X chromosomes may be inactivated. Therefore, special test statistics and quality control procedures are required. Thus, little is known about the role of X-chromosomal variants in CAD. To fill this gap, we conducted a comprehensive X-chromosome-wide meta-analysis including more than 43,000 CAD cases and 58,000 controls from 35 international study cohorts. For quality control, sex-specific filters were used to adequately take the special structure of X-chromosomal data into account. For single study analyses, several logistic regression models were calculated allowing for inactivation of one female X-chromosome, adjusting for sex and investigating interactions between sex and genetic variants. Then, meta-analyses including all 35 studies were conducted using random effects models. None of the investigated models revealed genome-wide significant associations for any variant. Although we analyzed the largest-to-date sample, currently available methods were not able to detect any associations of X-chromosomal variants with CAD.