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We examined the genetic background of nonalcoholic fatty liver disease (NAFLD) in the Japanese population, by performing a genome-wide association study (GWAS). For GWAS, 392 Japanese NAFLD subjects and 934 control individuals were analyzed. For replication studies, 172 NAFLD and 1,012 control subjects were monitored. After quality control, 261,540 single-nucleotide polymorphisms (SNPs) in autosomal chromosomes were analyzed using a trend test. Association analysis was also performed using multiple logistic regression analysis using genotypes, age, gender and body mass index (BMI) as independent variables. Multiple linear regression analyses were performed to evaluate allelic effect of significant SNPs on biochemical traits and histological parameters adjusted by age, gender, and BMI. Rs738409 in the PNPLA3 gene was most strongly associated with NAFLD after adjustment ( P  = 6.8 × 10 −14 , OR = 2.05). Rs2896019, and rs381062 in the PNPLA3 gene, rs738491, rs3761472, and rs2143571 in the SAMM50  gene, rs6006473, rs5764455, and rs6006611 in the PARVB gene had also significant P values (<2.0 × 10 −10 ) and high odds ratios (1.84–2.02). These SNPs were found to be in the same linkage disequilibrium block and were associated with decreased serum triglycerides and increased aspartate aminotransferase (AST) and alanine aminotransferase (ALT) in NAFLD patients. These SNPs were associated with steatosis grade and NAFLD activity score (NAS). Rs738409, rs2896019, rs738491, rs6006473, rs5764455, and rs6006611 were associated with fibrosis. Polymorphisms in the SAMM50 and PARVB genes in addition to those in the PNPLA3 gene were observed to be associated with the development and progression of NAFLD.

Selecting a set of valid genetic variants is critical for Mendelian randomization (MR) to correctly infer risk factors causing a disease. We here developed a method for selecting genetic variants as valid instrumental variables for inferring risk factors causing coronary artery disease (CAD). Using this method, we selected two sets of single-nucleotide-polymorphism (SNP) genetic variants (SNP338 and SNP363) associated with each of the three potential risk factors for CAD including low density lipoprotein cholesterol (LDL-c), high density lipoprotein cholesterol (HDL-c) and triglycerides (TG) from two independent GWAS datasets. We performed in-depth multivariate MR (MVMR) analyses and the results from both datasets consistently showed that LDL-c was strongly associated with increased risk for CAD ( β = 0.396,OR = 1.486 per 1 SD (equivalent to 38 mg/dL), 95CI = (1.38, 1.59) in SNP338; and β = 0.424, OR = 1.528 per 1 SD, 95%CI = (1.42, 1.65) in SNP363); HDL-c was strongly associated with reduced risk for CAD ( β = −0.315, OR = 0.729 per 1 SD (equivalent to 16 mg/dL), 95CI = (0.68, 0.78) in SNP338; and β = −0.319, OR = 0.726 per 1 SD, 95%CI = (0.66, 0.80), in SNP363). In case of TG, when using the full datasets, an increased risk for CAD ( β = 0.184, OR = 1.2 per 1 SD (equivalent to 89 mg/dL), 95%CI = (1.12, 1.28) in SNPP338; and β = 0.207, OR = 1.222 per 1 SD, 95%CI = (1.10, 1.36) in SNP363) was observed, while using partial datasets that contain shared and unique SNPs showed that TG is not a risk factor for CAD. From these results, it can be inferred that TG itself is not a causal risk factor for CAD, but it’s shown as a risk factor due to pleiotropic effects associated with LDL-c and HDL-c SNPs. Large-scale simulation experiments without pleiotropic effects also corroborated these results.

Observational studies have shown consistent associations between higher circulating 25-hydroxyvitamin D[25(OH)D] levels and favorable serum lipids. We sought to investigate if such associations were causal. A Mendelian randomization (MR) study was conducted on a population-based cohort comprising 56,435 adults in Norway. A weighted 25(OH)D allele score was generated based on vitamin D-increasing alleles of rs2282679, rs12785878 and rs10741657. Linear regression analyses of serum lipid levels on the allele score were performed to assess the presence of causal associations of serum 25(OH)D with the lipids. To quantify the causal effects, the inverse-variance weighted method was used for calculating MR estimates based on summarized data of individual single-nucleotide polymorphisms. The MR estimate with 95% confidence interval (CI) represents percentage difference in the lipid level per genetically determined 25 nmol/L increase in 25(OH)D. The 25(OH)D allele score demonstrated a clear association with high-density lipoprotein (HDL) cholesterol (p = 0.007) but no association with total or non-HDL cholesterol or triglycerides (p = 0.27). The MR estimate showed 2.52% (95% CI 0.79–4.25%) increase in HDL cholesterol per genetically determined 25 nmol/L increase in 25(OH)D, which was stronger than the corresponding estimate of 1.83% (95% CI 0.85–2.81%) from the observational analysis. The MR estimates for total cholesterol (0.60%, 95% CI-0.73 to 1.94%), non-HDL cholesterol (0.04%, 95% CI-1.79 to 1.88%) and triglycerides (-2.74%, 95% CI-6.16 to 0.67%) showed no associations. MR analysis of data from a population-based cohort suggested a causal and positive association between serum 25(OH)D and HDL cholesterol.

Weight-loss interventions generally improve lipid profiles and reduce cardiovascular disease risk, but effects are variable and may depend on genetic factors. We performed a genetic association analysis of data from 2,993 participants in the Diabetes Prevention Program to test the hypotheses that a genetic risk score (GRS) based on deleterious alleles at 32 lipid-associated single-nucleotide polymorphisms modifies the effects of lifestyle and/or metformin interventions on lipid levels and nuclear magnetic resonance (NMR) lipoprotein subfraction size and number. Twenty-three loci previously associated with fasting LDL-C, HDL-C, or triglycerides replicated (P = 0.04-1 × 10(-17)). Except for total HDL particles (r = -0.03, P = 0.26), all components of the lipid profile correlated with the GRS (partial |r| = 0.07-0.17, P = 5 × 10(-5)-1 10(-19)). The GRS was associated with higher baseline-adjusted 1-year LDL cholesterol levels (β = +0.87, SEE ± 0.22 mg/dl/allele, P = 8 × 10(-5), P(interaction) = 0.02) in the lifestyle intervention group, but not in the placebo (β = +0.20, SEE ± 0.22 mg/dl/allele, P = 0.35) or metformin (β = -0.03, SEE ± 0.22 mg/dl/allele, P = 0.90; P(interaction) = 0.64) groups. Similarly, a higher GRS predicted a greater number of baseline-adjusted small LDL particles at 1 year in the lifestyle intervention arm (β = +0.30, SEE ± 0.012 ln nmol/L/allele, P = 0.01, P(interaction) = 0.01) but not in the placebo (β = -0.002, SEE ± 0.008 ln nmol/L/allele, P = 0.74) or metformin (β = +0.013, SEE ± 0.008 nmol/L/allele, P = 0.12; P(interaction) = 0.24) groups. Our findings suggest that a high genetic burden confers an adverse lipid profile and predicts attenuated response in LDL-C levels and small LDL particle number to dietary and physical activity interventions aimed at weight loss.

Mendelian randomization (MR) is an epidemiological technique that uses genetic variants to distinguish correlation from causation in observational data. The reliability of a MR investigation depends on the validity of the genetic variants as instrumental variables (IVs). We develop the contamination mixture method, a method for MR with two modalities. First, it identifies groups of genetic variants with similar causal estimates, which may represent distinct mechanisms by which the risk factor influences the outcome. Second, it performs MR robustly and efficiently in the presence of invalid IVs. Compared to other robust methods, it has the lowest mean squared error across a range of realistic scenarios. The method identifies 11 variants associated with increased high-density lipoprotein-cholesterol, decreased triglyceride levels, and decreased coronary heart disease risk that have the same directions of associations with various blood cell traits, suggesting a shared mechanism linking lipids and coronary heart disease risk mediated via platelet aggregation. Mendelian randomization (MR) is a method for inferring causal relationships between risk factors and outcomes via associated genetic variants. Here, Burgess et al. develop the contamination mixture method which yields robust MR results in the presence of invalid instrumental variables and groups variants by their effect estimates.

Sekar Kathiresan and colleagues examine 185 common variants using a modified mendelian randomization approach and provide evidence supporting a causal role of triglyceride-rich lipoproteins in the development of coronary artery disease. Triglycerides are transported in plasma by specific triglyceride-rich lipoproteins; in epidemiological studies, increased triglyceride levels correlate with higher risk for coronary artery disease (CAD). However, it is unclear whether this association reflects causal processes. We used 185 common variants recently mapped for plasma lipids ( P < 5 × 10 −8 for each) to examine the role of triglycerides in risk for CAD. First, we highlight loci associated with both low-density lipoprotein cholesterol (LDL-C) and triglyceride levels, and we show that the direction and magnitude of the associations with both traits are factors in determining CAD risk. Second, we consider loci with only a strong association with triglycerides and show that these loci are also associated with CAD. Finally, in a model accounting for effects on LDL-C and/or high-density lipoprotein cholesterol (HDL-C) levels, the strength of a polymorphism's effect on triglyceride levels is correlated with the magnitude of its effect on CAD risk. These results suggest that triglyceride-rich lipoproteins causally influence risk for CAD.

Cristen Willer and colleagues report genome-wide association analyses for blood lipid levels in 188,578 individuals. They identify 62 loci newly associated with blood lipid levels, refine the association signals at 12 loci and examine associations with cardiovascular and metabolic traits. Levels of low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides and total cholesterol are heritable, modifiable risk factors for coronary artery disease. To identify new loci and refine known loci influencing these lipids, we examined 188,577 individuals using genome-wide and custom genotyping arrays. We identify and annotate 157 loci associated with lipid levels at P < 5 × 10 −8 , including 62 loci not previously associated with lipid levels in humans. Using dense genotyping in individuals of European, East Asian, South Asian and African ancestry, we narrow association signals in 12 loci. We find that loci associated with blood lipid levels are often associated with cardiovascular and metabolic traits, including coronary artery disease, type 2 diabetes, blood pressure, waist-hip ratio and body mass index. Our results demonstrate the value of using genetic data from individuals of diverse ancestry and provide insights into the biological mechanisms regulating blood lipids to guide future genetic, biological and therapeutic research.

Searching for genes in which loss-of-function mutations confer protection against disease is a strategy to identity drug targets. This study reports an association between loss-of-function mutations in ANGPTL4 and protection against coronary artery disease. Although genomewide association studies have identified more than 56 loci associated with the risk of coronary artery disease, 1 – 3 the disease-associated variants are typically common (minor-allele frequency >5%) and located in noncoding sequences; this has made it difficult to pinpoint causal genes and affected pathways. This lack of a causal mechanism has in part hindered the immediate translation of the findings of genomewide association studies into new therapeutic targets. However, the discovery of rare or low-frequency coding-sequence variants that affect the risk of coronary artery disease has facilitated advances in the prevention and treatment of disease. The most recent example . . .

Latin America continues to be severely underrepresented in genomics research, and fine-scale genetic histories and complex trait architectures remain hidden owing to insufficient data 1 . To fill this gap, the Mexican Biobank project genotyped 6,057 individuals from 898 rural and urban localities across all 32 states in Mexico at a resolution of 1.8 million genome-wide markers with linked complex trait and disease information creating a valuable nationwide genotype–phenotype database. Here, using ancestry deconvolution and inference of identity-by-descent segments, we inferred ancestral population sizes across Mesoamerican regions over time, unravelling Indigenous, colonial and postcolonial demographic dynamics 2 – 6 . We observed variation in runs of homozygosity among genomic regions with different ancestries reflecting distinct demographic histories and, in turn, different distributions of rare deleterious variants. We conducted genome-wide association studies (GWAS) for 22 complex traits and found that several traits are better predicted using the Mexican Biobank GWAS compared to the UK Biobank GWAS 7 , 8 . We identified genetic and environmental factors associating with trait variation, such as the length of the genome in runs of homozygosity as a predictor for body mass index, triglycerides, glucose and height. This study provides insights into the genetic histories of individuals in Mexico and dissects their complex trait architectures, both crucial for making precision and preventive medicine initiatives accessible worldwide. Nationwide genomic biobank in Mexico unravels demographic history and complex trait architecture from 6,057 individuals.

Fatty liver disease (FLD) is a disorder in which accumulation of triglycerides (TGs) in the liver can lead to inflammation, fibrosis, and cirrhosis. Previously, we identified a variant (I148M) in patatin-like phospholipase domain-containing protein 3 (PNPLA3) that is strongly associated with FLD, but the mechanistic basis for the association remains elusive. Although PNPLA3 has TG hydrolase activity in vitro, inactivation or overexpression of the WT protein in mice does not cause steatosis. In contrast, expression of two catalytically defective forms of PNPLA3 (I148M or S47A) in sucrose-fed mice causes accumulation of both PNPLA3 and TGs on hepatic lipid droplets (LDs). To determine if amassing PNPLA3 on LDs is a cause or consequence of steatosis, we engineered a synthetic isoform of PNPLA3 that uncouples protein accumulation from loss of enzymatic activity. Expression of a ubiquitylation-resistant form of PNPLA3 in mice caused accumulation of PNPLA3 on hepatic LDs and development of FLD. Lowering PNPLA3 levels by either shRNA knockdown or proteolysis-targeting chimera (PROTAC)-mediated degradation reduced liver TG content in mice overexpressing PNPLA3(148M). Taken together, our results show that the steatosis associated with PNPLA3(148M) is caused by accumulation of PNPLA3 on LDs.