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Given the polygenic nature of antipsychotic-induced weight gain (AIWG), we investigated whether polygenic risk scores (PRS) for various psychiatric and metabolic traits were associated with AIWG. We included individuals with schizophrenia (SCZ) of European ancestry from two cohorts (N = 151, age = 40.3 ± 11.8 and N = 138, age = 36.5 ± 10.8). We investigated associations of AIWG defined as binary and continuous variables with PRS calculated from genome-wide association studies of body mass index (BMI), coronary artery disease (CAD), fasting glucose, fasting insulin, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol (LDL-C), triglycerides, type 1 and 2 diabetes mellitus, and SCZ, using regression models. We observed nominal associations (uncorrected p < 0.05) between PRSs for BMI, CAD, and LDL-C, type 1 diabetes, and SCZ with AIWG. While results became non-significant after correction for multiple testing, these preliminary results suggest that PRS analyses might contribute to identifying risk factors of AIWG and might help to elucidate mechanisms at play in AIWG., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

Genetic associations for lipid traits have identified hundreds of variants with clear differences across European, Asian and African studies. Based on a sub-Saharan-African GWAS for lipid traits in the population cross-sectional AWI-Gen cohort (N = 10,603) we report a novel LDL-C association in the GATB region (P-value=1.56 × 10 -8 ). Meta-analysis with four other African cohorts (N = 23,718) provides supporting evidence for the LDL-C association with the GATB/FHIP1A region and identifies a novel triglyceride association signal close to the FHIT gene (P-value =2.66 × 10 -8 ). Our data enable fine-mapping of several well-known lipid-trait loci including LDLR, PMFBP1 and LPA. The transferability of signals detected in two large global studies (GLGC and PAGE) consistently improves with an increase in the size of the African replication cohort. Polygenic risk score analysis shows increased predictive accuracy for LDL-C levels with the narrowing of genetic distance between the discovery dataset and our cohort. Novel discovery is enhanced with the inclusion of African data., (© 2022. The Author(s).)

Familial hypercholesterolemia (FH) is an autosomal dominant monogenic disorder characterized by elevated levels of low-density lipoprotein cholesterol (LDL-C) and an increased risk of premature coronary artery disease (CAD). Recently, it has been shown that a high polygenic risk score (PRS) could be an independent risk factor for CAD in FH patients of European ancestry. However, it is uncertain whether PRS is also useful for risk stratification of FH patients in East Asia. We recruited and genotyped clinically diagnosed FH (CDFH) patients from the Kanazawa University Mendelian Disease FH registry and controls from the Shikamachi Health Improvement Practice genome cohort in Japan. We calculated PRS from 3.6 million variants of each participant (imputed from the 1000 Genome phase 3 Asian dataset) for LDL-C (PRS LDLC ) using a genome-wide association study summary statistic from the BioBank Japan Project. We assessed the association of PRS LDLC with LDL-C and CAD among and within monogenic FH, mutation negative CDFH, and controls. We tested a total of 1223 participants (376 FH patients, including 173 with monogenic FH and 203 with mutation negative CDFH, and 847 controls) for the analyses. PRS LDLC was significantly higher in mutation negative CDFH patients than in controls (p = 3.1 × 10 -13 ). PRS LDLC was also significantly linked to LDL-C in controls (p trend = 3.6 × 10 -4 ) but not in FH patients. Moreover, we could not detect any association between PRS LDLC and CAD in any of the groups. In conclusion, mutation negative CDFH patients demonstrated significantly higher PRS LDLC than controls. However, PRS LDLC may have little additional effect on LDL-C and CAD among FH patients., (© 2021. The Author(s), under exclusive licence to The Japan Society of Human Genetics.)

It remains unclear whether the increased risk of new-onset type 2 diabetes (T2D) seen in statin users is due to low LDL-C concentrations, or due to the statin-induced proportional change in LDL-C. In addition, genetic instruments have not been proposed before to examine whether liability to T2D might cause greater proportional statin-induced LDL-C lowering. Using summary-level statistics from the Genomic Investigation of Statin Therapy (GIST, n max  = 40,914) and DIAGRAM (n max  = 159,208) consortia, we found a positive genetic correlation between LDL-C statin response and T2D using LD score regression (r genetic  = 0.36, s.e. = 0.13). However, mendelian randomization analyses did not provide support for statin response having a causal effect on T2D risk (OR 1.00 (95% CI: 0.97, 1.03) per 10% increase in statin response), nor that liability to T2D has a causal effect on statin-induced LDL-C response (0.20% increase in response (95% CI: -0.40, 0.80) per doubling of odds of liability to T2D). Although we found no evidence to suggest that proportional statin response influences T2D risk, a definitive assessment should be made in populations comprised exclusively of statin users, as the presence of nonstatin users in the DIAGRAM dataset may have substantially diluted our effect estimate.

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.

Rare genetic disorders (RGDs) often exhibit significant clinical variability among affected individuals, a disease characteristic termed variable expressivity. Recently, the aggregate effect of common variation, quantified as polygenic scores (PGSs), has emerged as an effective tool for predictions of disease risk and trait variation in the general population. Here, we measure the effect of PGSs on 11 RGDs including four sex-chromosome aneuploidies (47,XXX; 47,XXY; 47,XYY; 45,X) that affect height; two copy-number variant (CNV) disorders (16p11.2 deletions and duplications) and a Mendelian disease (melanocortin 4 receptor deficiency (MC4R)) that affect BMI; and two Mendelian diseases affecting cholesterol: familial hypercholesterolemia (FH; LDLR and APOB) and familial hypobetalipoproteinemia (FHBL; PCSK9 and APOB). Our results demonstrate that common, polygenic factors of relevant complex traits frequently contribute to variable expressivity of RGDs and that PGSs may be a useful metric for predicting clinical severity in affected individuals and for risk stratification.

Lipids foster energy production and their altered levels have been coupled with metabolic ailments. Indians feature high prevalence of metabolic diseases, yet uncharacterized for genes regulating lipid homeostasis. We performed first GWAS for quantitative lipids (total cholesterol, LDL, HDL, and triglycerides) exclusively in 5271 Indians. Further to corroborate our genetic findings, we investigated DNA methylation marks in peripheral blood in Indians at the identified loci (N = 233) and retrieved gene regulatory features from public domains. Recurrent GWAS loci-CELSR2, CETP, LPL, ZNF259, and BUD13 cropped up as lead signals in Indians, reflecting their universal applicability. Besides established variants, we found certain unreported variants at sub-genome-wide level-QKI, REEP3, TMCC2, FAM129C, FAM241B, and LOC100506207. These variants though failed to attain GWAS significance in Indians, but largely turned out to be active CpG sites in human subcutaneous adipose tissue and showed robust association to two or more lipid traits. Of which, QKI variants showed significant association to all four lipid traits and their designated region was observed to be a key gene regulatory segment denoting active transcription particularly in human subcutaneous adipose tissue. Both established and novel loci were observed to be significantly associated with altered DNA methylation in Indians for specific CpGs that resided in key regulatory elements. Further, gene-based association analysis pinpointed novel GWAS loci-LINC01340 and IQCJ-SCHIP1 for TC; IFT27, IFT88, and LINC02141 for HDL; and TEX26 for TG. Present study ascertains universality of selected known genes and also identifies certain novel loci for lipids in Indians by integrating data from various levels of gene regulation.

Many genetic loci affect circulating lipid levels, but it remains unknown whether lifestyle factors, such as physical activity, modify these genetic effects. To identify lipid loci interacting with physical activity, we performed genome-wide analyses of circulating HDL cholesterol, LDL cholesterol, and triglyceride levels in up to 120,979 individuals of European, African, Asian, Hispanic, and Brazilian ancestry, with follow-up of suggestive associations in an additional 131,012 individuals. We find four loci, in/near CLASP1, LHX1, SNTA1, and CNTNAP2, that are associated with circulating lipid levels through interaction with physical activity; higher levels of physical activity enhance the HDL cholesterol-increasing effects of the CLASP1, LHX1, and SNTA1 loci and attenuate the LDL cholesterol-increasing effect of the CNTNAP2 locus. The CLASP1, LHX1, and SNTA1 regions harbor genes linked to muscle function and lipid metabolism. Our results elucidate the role of physical activity interactions in the genetic contribution to blood lipid levels.

Large-scale deep-coverage whole-genome sequencing (WGS) is now feasible and offers potential advantages for locus discovery. We perform WGS in 16,324 participants from four ancestries at mean depth >29X and analyze genotypes with four quantitative traits-plasma total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol, and triglycerides. Common variant association yields known loci except for few variants previously poorly imputed. Rare coding variant association yields known Mendelian dyslipidemia genes but rare non-coding variant association detects no signals. A high 2M-SNP LDL-C polygenic score (top 5th percentile) confers similar effect size to a monogenic mutation (~30 mg/dl higher for each); however, among those with severe hypercholesterolemia, 23% have a high polygenic score and only 2% carry a monogenic mutation. At these sample sizes and for these phenotypes, the incremental value of WGS for discovery is limited but WGS permits simultaneous assessment of monogenic and polygenic models to severe hypercholesterolemia.

Interleukin 6 receptor (IL-6R), mediating IL-6's biological functions, plays an important role in different diseases such as diabetes, obesity and cardio-vascular diseases. In this study, we investigated the effects of two single nucleotide polymorphisms (SNPs), within the IL-6R loci, previously associated with C-reactive protein (CRP) and coronary heart diseases risk, and with controversial effects on lipids traits: SNP rs4845625 and SNP rs4537545. The results showed that both investigated SNPs were antagonistically related with CRP levels; the minor rs4845625*T allele was associated with increased CRP levels (P-value=0.011), while the minor rs4537545*T allele was associated with decreased CRP levels (P-value=0.009). Interestingly, the minor rs4845625*T allele was significantly associated with higher low-density lipoprotein cholesterol (LDL-C) and ApoB levels (P=0.007 and P=0.009 respectively). Haplotype analysis showed that the TC haplotype, having the minor rs4845625*T allele, was related simultaneously with increased levels of CRP, LDL-C and ApoB levels, thus could be considered as a risk factor. Our investigation detects for the first time an independent effect of rs4845625 on LDL-C and ApoB traits, explaining an important range of those traits variability (3.49 and 5.57% respectively). Our findings might be of high clinical significance in pharmacogenomics studies of tocilizumab for which IL-6R is target.

In humans and animals lacking functional LDL receptor (LDLR), LDL from plasma still readily traverses the endothelium. To identify the pathways of LDL uptake, a genome-wide RNAi screen was performed in endothelial cells and cross-referenced with GWAS-data sets. Here we show that the activin-like kinase 1 (ALK1) mediates LDL uptake into endothelial cells. ALK1 binds LDL with lower affinity than LDLR and saturates only at hypercholesterolemic concentrations. ALK1 mediates uptake of LDL into endothelial cells via an unusual endocytic pathway that diverts the ligand from lysosomal degradation and promotes LDL transcytosis. The endothelium-specific genetic ablation of Alk1 in Ldlr-KO animals leads to less LDL uptake into the aortic endothelium, showing its physiological role in endothelial lipoprotein metabolism. In summary, identification of pathways mediating LDLR-independent uptake of LDL may provide unique opportunities to block the initiation of LDL accumulation in the vessel wall or augment hepatic LDLR-dependent clearance of LDL., Competing Interests: M.W.N. is an employee of Pfizer Worldwide Research and Development, but the company had no influence in study design, data collection and analyses. Other authors declare no competing financial interests.

Statins effectively lower LDL cholesterol levels in large studies and the observed interindividual response variability may be partially explained by genetic variation. Here we perform a pharmacogenetic meta-analysis of genome-wide association studies (GWAS) in studies addressing the LDL cholesterol response to statins, including up to 18,596 statin-treated subjects. We validate the most promising signals in a further 22,318 statin recipients and identify two loci, SORT1/CELSR2/PSRC1 and SLCO1B1, not previously identified in GWAS. Moreover, we confirm the previously described associations with APOE and LPA. Our findings advance the understanding of the pharmacogenetic architecture of statin response.

The LDL receptor has an essential role in regulating plasma LDL-C levels. Genetic variation in the LDLR gene can be associated with either lower or moderately raised plasma levels of LDL-C, or may cause familial hypercholesterolemia. The prevalence of single-nucleotide polymorphisms (SNPs) in the LDLR in the black South African population is not known and therefore, we aimed to determine the genotypic variation of the LDLR in the study population as well as to define the association of the different genotypes with plasma LDL-C levels. A random selection of 1860 apparently healthy black South African volunteers aged 35-60 years was made in a cross-sectional study. Novel SNPs were identified in a subset of 30 individuals by means of automated sequencing before screening the entire cohort by means of the Illumina VeraCode GoldenGate Genotyping Assay on a BeadXpress Reader system. Twenty-five SNPs were genotyped, two of which were novel. A very rare SNP, rs17249141, in the promoter region was significantly associated with lower levels of LDL-C. Four other SNPs (rs2738447, rs14158, rs2738465 and rs3180023) were significantly associated with increased levels of LDL-C. We can conclude that some of the various SNPs identified do indeed associate with LDL-C levels.

It was investigated whether pharmacogenetic factors, both as single polymorphism and as gene-gene interactions, have an added value over non-genetic factors in predicting statin response. Five common polymorphisms were selected in apolipoprotein E, angiotensin-converting enzyme, hepatic lipase and toll-like receptor 4. Linear regression models were built and compared on R(2) to estimate the added value of single polymorphisms and gene-gene interactions. The selected polymorphisms and the gene-gene interactions had a small added value in predicting change in low-density lipoprotein cholesterol levels (LDL-c) as response to statins over the non-genetic predictors (P=0.104), and also in predicting LDL-c in non-treated patients (P=0.016). Moreover, four gene-gene interactions with statin therapy were identified. The added value of genetic factors over non-genetic variables is for the greater part produced by gene-gene interactions. This underlines the importance to examine gene-gene interactions in future (pharmaco)genetic research.

As a peroxisome proliferator-activated receptor alpha (PPARα) agonist, fenofibrate favorably modulates dyslipidemia and inflammation markers, which are associated with cardiovascular risk. To determine whether variation in the PPARα receptor gene was associated with lipid and inflammatory marker response, we conducted a 3-week trial of fenofibrate in 861 men and women. Mixed linear models that controlled for age and sex, as well as family pedigree and study center, were constructed using single-nucleotide polymorphisms (SNPs) in the PPARα gene as predictors and changes in fasting triglycerides (TGs), cholesterol and inflammatory markers as outcomes. Significant associations with low-density cholesterol and interleukin-2 (P<0.001) responses to fenofibrate were found. Although there were suggestive associations with tumor necrosis factor-alpha and TG responses (P<0.05), these did not survive the correction for multiple testing. We conclude that variants in the PPARα gene may contribute to future pharmacogenomic paradigms seeking to predict fenofibrate responders from both an anti-dyslipidemic and anti-inflammatory perspective.

Over the past decade, large multicenter trials have unequivocally demonstrated that decreasing low-density lipoprotein (LDL) cholesterol can reduce both primary and secondary cardiovascular events in patients at risk. However, even in the context of maximal LDL lowering, there remains considerable residual cardiovascular risk. Some of this risk can be attributed to variability in high-density lipoprotein (HDL) cholesterol. As such, there is tremendous interest in defining determinants of HDL homeostasis. Risk prediction models are being constructed based upon (1) clinical contributors, (2) known molecular determinants and (3) the genetic architecture underlying HDL cholesterol levels. To date, however, no single resource has combined these factors within the context of a practice-based data set. Recently, a number of academic medical centers have begun constructing DNA biobanks linked to secure encrypted versions of their respective electronic medical record. As these biobanks combine resources, the clinical community is in a position to characterize lipid-related treatment outcome on an unprecedented scale.

We have reported that the sequence variation in the tenomodulin (TNMD) gene is associated with the risk of type 2 diabetes (T2DM), central obesity and serum levels of systemic immune mediators in the Finnish Diabetes Prevention Study (DPS), which is a longitudinal lifestyle intervention study on 522 middle-aged persons with impaired glucose tolerance (IGT). The aim of this study was to investigate whether the association with T2DM, observed in the DPS could be replicated in a larger, cross-sectional population-based random sample of 5298 men (3020 with normoglycaemia, 984 with impaired fasting glucose, 436 with IGT and 811 with T2DM) from the region of Kuopio, eastern Finland. To further explore the putative mechanisms linking TNMD to T2DM and metabolic syndrome, we studied the associations of TNMD sequence variation with lipid abnormalities characteristic to metabolic syndrome. The association with T2DM risk was not replicated, but significant associations were found with serum low-density lipoprotein and total cholesterol in a body mass index-dependent manner. These associations were also observed in the men of DPS, whereas in women these associations were not significant. These results from two independent study populations suggest that the genetic variation in TNMD could modulate cholesterol metabolism in obese men.

Genetic factors, alone or in interaction with components of the diet, are thought to be involved in the development of the metabolic syndrome. The objective of our study was first to compare the frequency of the peroxisome proliferator-activated receptor (PPAR)alpha-L162V polymorphism in a sample of men with and without the metabolic syndrome as defined by the National Cholesterol Education Program-Adult Treatment Panel III (NCEP-ATPIII) guidelines, and secondly, to evaluate gene-diet interaction effects on features of the metabolic syndrome. The PPARalpha-L162V genotype was determined in a sample of 632 men by a polymerase chain reaction-restriction length polymorphism (PCR-RFLP)-based method; fat as well as saturated fat intakes were evaluated by a dietitian-administered food frequency questionnaire. The frequency of the V162 allele was similar in men with ( n=281) and without ( n=351) the metabolic syndrome ( chi(2)=0.03, p=0.84) but was higher in subjects having simultaneously abdominal obesity, hypertriglyceridemia, and low high-density lipoprotein cholesterol (HDL-C) levels ( chi(2)=3.73, p=0.05). Carriers of the V162 were characterized by higher plasma apolipoprotein B and triglyceride (TG) levels ( p=0.10, p=0.004). In a model including the PPARalpha-L162V polymorphism, fat or saturated fat, its interaction, and covariates (smoking habits, and energy and alcohol intake), the interaction explained a significant percentage of the variance observed in waist circumference ( p<0.05). In conclusion, the PPARalpha-L162V polymorphism alone or in interaction with dietary fat intake is associated with components of the metabolic syndrome.