Inferring causal direction between two traits using R2 with application to transcriptome-wide association studies.

In Mendelian randomization, two single SNP-trait correlation-based methods have been developed to infer the causal direction between an exposure (e.g., a gene) and an outcome (e.g., a trait), called MR Steiger's method and its recent extension called Causal Direction-Ratio (CD-Ratio). Here we propose an approach based on R2, the coefficient of determination, to combine information from multiple (possibly correlated) SNPs to simultaneously infer the presence and direction of a causal relationship between an exposure and an outcome. Our proposed method generalizes Steiger's method from using a single SNP to multiple SNPs as IVs. It is especially useful in transcriptome-wide association studies (TWASs) (and similar applications) with typically small sample sizes for gene expression (or another molecular trait) data, providing a more flexible and powerful approach to inferring causal directions. It can be applied to GWAS summary data with a reference panel. We also discuss the influence of invalid IVs and introduce a new approach called R2S to select and remove invalid IVs (if any) to enhance the robustness. We compared the performance of the proposed method with existing methods in simulations to demonstrate its advantages. We applied the methods to identify causal genes for high/low-density lipoprotein cholesterol (HDL/LDL) using the individual-level GTEx gene expression data and UK Biobank GWAS data. The proposed method was able to confirm some well-known causal genes while identifying some novel ones. Additionally, we illustrated an application of the proposed method to GWAS summary to infer causal relationships between HDL/LDL and stroke/coronary artery disease (CAD).

Correlation-based tests for the formal comparison of polygenic scores in multiple populations.

Polygenic scores (PGS) are measures of genetic risk, derived from the results of genome wide association studies (GWAS). Previous work has proposed the coefficient of determination (R2) as an appropriate measure by which to compare PGS performance in a validation dataset. Here we propose correlation-based methods for evaluating PGS performance by adapting previous work which produced a statistical framework and robust test statistics for the comparison of multiple correlation measures in multiple populations. This flexible framework can be extended to a wider variety of hypothesis tests than currently available methods. We assess our proposed method in simulation and demonstrate its utility with two examples, assessing previously developed PGS for low-density lipoprotein cholesterol and height in multiple populations in the All of Us cohort. Finally, we provide an R package 'coranova' with both parametric and nonparametric implementations of the described methods.

Co-methylation analyses identify CpGs associated with lipid traits in Chinese discordant monozygotic twins.

To control genetic background and early life milieu in genome-wide DNA methylation analysis for blood lipids, we recruited Chinese discordant monozygotic twins to explore the relationships between DNA methylations and total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG). 132 monozygotic (MZ) twins were included with discordant lipid levels and completed data. A linear mixed model was conducted in Epigenome-wide association study (EWAS). Generalized estimating equation model was for gene expression analysis. We conducted Weighted correlation network analysis (WGCNA) to build co-methylated interconnected network. Additional Qingdao citizens were recruited for validation. Inference about Causation through Examination of Familial Confounding (ICE FALCON) was used to infer the possible direction of these relationships. A total of 476 top CpGs reached suggestively significant level (P < 10-4), of which, 192 CpGs were significantly associated with TG (FDR < 0.05). They were used to build interconnected network and highlight crucial genes from WGCNA. Finally, four CpGs in GATA4 were validated as risk factors for TC; six CpGs at ITFG2-AS1 were negatively associated with TG; two CpGs in PLXND1 played protective roles in HDL-C. ICE FALCON indicated abnormal TC was regarded as the consequence of DNA methylation in CpGs at GATA4, rather than vice versa. Four CpGs in ITFG2-AS1 were both causes and consequences of modified TG levels. Our results indicated that DNA methylation levels of 12 CpGs in GATA4, ITFG2-AS1, and PLXND1 were relevant to TC, TG, and HDL-C, respectively, which might provide new epigenetic insights into potential clinical treatment of dyslipidemia.

Identification and analysis of individuals who deviate from their genetically-predicted phenotype.

Findings from genome-wide association studies have facilitated the generation of genetic predictors for many common human phenotypes. Stratifying individuals misaligned to a genetic predictor based on common variants may be important for follow-up studies that aim to identify alternative causal factors. Using genome-wide imputed genetic data, we aimed to classify 158,951 unrelated individuals from the UK Biobank as either concordant or deviating from two well-measured phenotypes. We first applied our methods to standing height: our primary analysis classified 244 individuals (0.15%) as misaligned to their genetically predicted height. We show that these individuals are enriched for self-reporting being shorter or taller than average at age 10, diagnosed congenital malformations, and rare loss-of-function variants in genes previously catalogued as causal for growth disorders. Secondly, we apply our methods to LDL cholesterol (LDL-C). We classified 156 (0.12%) individuals as misaligned to their genetically predicted LDL-C and show that these individuals were enriched for both clinically actionable cardiovascular risk factors and rare genetic variants in genes previously shown to be involved in metabolic processes. Individuals whose LDL-C was higher than expected based on the genetic predictor were also at higher risk of developing coronary artery disease and type-two diabetes, even after adjustment for measured LDL-C, BMI and age, suggesting upward deviation from genetically predicted LDL-C is indicative of generally poor health. Our results remained broadly consistent when performing sensitivity analysis based on a variety of parametric and non-parametric methods to define individuals deviating from polygenic expectation. Our analyses demonstrate the potential importance of quantitatively identifying individuals for further follow-up based on deviation from genetic predictions.

Evinacumab for Pediatric Patients With Homozygous Familial Hypercholesterolemia.

BACKGROUND: Homozygous familial hypercholesterolemia (HoFH) is a rare genetic disorder characterized by severely elevated low-density lipoprotein cholesterol (LDL-C) levels due to profoundly defective LDL receptor (LDLR) function. Given that severely elevated LDL-C starts in utero, atherosclerosis often presents during childhood or adolescence, creating a largely unmet need for aggressive LDLR-independent lipid-lowering therapies in young patients with HoFH. Here we present the first evaluation of the efficacy and safety of evinacumab, a novel LDLR-independent lipid-lowering therapy, in pediatric patients with HoFH from parts A and B of a 3-part study. METHODS: The phase 3, part B, open-label study treated 14 patients 5 to 11 years of age with genetically proven HoFH (true homozygotes and compound heterozygotes) with LDL-C >130 mg/dL, despite optimized lipid-lowering therapy (including LDLR-independent apheresis and lomitapide), with intravenous evinacumab 15 mg/kg every 4 weeks. RESULTS: Evinacumab treatment rapidly and durably (through week 24) decreased LDL-C with profound reduction in the first week, with a mean (SE) LDL-C reduction of -48.3% (10.4%) from baseline to week 24. ApoB (mean [SE], -41.3% [9.0%]), non-high-density lipoprotein cholesterol (-48.9% [9.8%]), and total cholesterol (-49.1% [8.1%]) were similarly decreased. Treatment-emergent adverse events were reported in 10 (71.4%) patients; however, only 2 (14.3%) reported events that were considered to be treatment-related (nausea and abdominal pain). One serious treatment-emergent adverse event of tonsillitis occurred (n=1), but this was not considered treatment-related. CONCLUSIONS: Evinacumab constitutes a new treatment for pediatric patients with HoFH and inadequately controlled LDL-C despite optimized lipid-lowering therapy, lowering LDL-C levels by nearly half in these extremely high-risk and difficult-to-treat individuals. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT04233918.

Association of lipid-lowering drugs with risk of sarcopenia: a drug target mendelian randomization study and meta-analysis.

BACKGROUND: Lipid-lowering drugs are widely used among the elderly, with some studies suggesting links to muscle-related symptoms. However, the causality remains uncertain. METHODS: Using the Mendelian randomization (MR) approach, we assessed the causal effects of genetically proxied reduced low-density lipoprotein cholesterol (LDL-C) through inhibitions of hydroxy-methyl-glutaryl-CoA reductase (HMGCR), proprotein convertase subtilisin/kexin type 9 (PCSK9), and Niemann-Pick C1-like 1 (NPC1L1) on sarcopenia-related traits, including low hand grip strength, appendicular lean mass, and usual walking pace. A meta-analysis was conducted to combine the causal estimates from different consortiums. RESULTS: Using LDL-C pooled data predominantly from UK Biobank, genetically proxied inhibition of HMGCR was associated with higher appendicular lean mass (beta = 0.087, P = 7.56 × 10- 5) and slower walking pace (OR = 0.918, P = 6.06 × 10- 9). In contrast, inhibition of PCSK9 may reduce appendicular lean mass (beta = -0.050, P = 1.40 × 10- 3), while inhibition of NPC1L1 showed no causal impact on sarcopenia-related traits. These results were validated using LDL-C data from Global Lipids Genetics Consortium, indicating that HMGCR inhibition may increase appendicular lean mass (beta = 0.066, P = 2.17 × 10- 3) and decelerate walking pace (OR = 0.932, P = 1.43 × 10- 6), whereas PCSK9 inhibition could decrease appendicular lean mass (beta = -0.048, P = 1.69 × 10- 6). Meta-analysis further supported the robustness of these causal associations. CONCLUSIONS: Genetically proxied HMGCR inhibition may increase muscle mass but compromise muscle function, PCSK9 inhibition could result in reduced muscle mass, while NPC1L1 inhibition is not associated with sarcopenia-related traits and this class of drugs may serve as viable alternatives to sarcopenia individuals or those at an elevated risk.

Genetic testing for familial hypercholesterolemia.

PURPOSE OF REVIEW: Despite familial hypercholesterolemia (FH) being the most common genetic cause of cardiovascular disease (CVD), genetic testing is rarely utilized in the US. This review summarizes what is known about the clinical utility of genetic testing and its role in the diagnosis and screening of FH. RECENT FINDINGS: The presence of an FH-causative variant is associated with a substantially higher risk of CVD, even when low-density lipoprotein cholesterol (LDL-C) levels are only modestly elevated. Genetic testing can facilitate the identification of FH cases who may be missed by clinical diagnostic criteria, improve risk stratification beyond LDL-C and family history, guide treatment decisions, and improve treatment initiation and adherence. Genetic testing can be incorporated into FH screening and diagnosis algorithms, including cascade, targeted, and universal screening. Integrating genetic testing into cascade screening can enhance the effectiveness of the process. Several models of universal FH screening with coordinated genetic and lipid testing are feasible and effective. SUMMARY: More systematic integration of genetic testing into FH diagnosis and screening can significantly reduce the burden of this condition through early detection and treatment. Further pragmatic implementation studies are needed to determine how to more effectively and affordably integrate genetic testing into clinical lipid screening programs.

Unraveling the genetic background of individuals with a clinical familial hypercholesterolemia phenotype.

Familial hypercholesterolemia (FH) is a common genetic disorder of lipid metabolism caused by pathogenic/likely pathogenic variants in LDLR, APOB, and PCSK9 genes. Variants in FH-phenocopy genes (LDLRAP1, APOE, LIPA, ABCG5, and ABCG8), polygenic hypercholesterolemia, and hyperlipoprotein (a) [Lp(a)] can also mimic a clinical FH phenotype. We aim to present a new diagnostic tool to unravel the genetic background of clinical FH phenotype. Biochemical and genetic study was performed in 1,005 individuals with clinical diagnosis of FH, referred to the Portuguese FH Study. A next-generation sequencing panel, covering eight genes and eight SNPs to determine LDL-C polygenic risk score and LPA genetic score, was validated, and used in this study. FH was genetically confirmed in 417 index cases: 408 heterozygotes and 9 homozygotes. Cascade screening increased the identification to 1,000 FH individuals, including 11 homozygotes. FH-negative individuals (phenotype positive and genotype negative) have Lp(a) >50 mg/dl (30%), high polygenic risk score (16%), other monogenic lipid metabolism disorders (1%), and heterozygous pathogenic variants in FH-phenocopy genes (2%). Heterozygous variants of uncertain significance were identified in primary genes (12%) and phenocopy genes (7%). Overall, 42% of our cohort was genetically confirmed with FH. In the remaining individuals, other causes for high LDL-C were identified in 68%. Hyper-Lp(a) or polygenic hypercholesterolemia may be the cause of the clinical FH phenotype in almost half of FH-negative individuals. A small part has pathogenic variants in ABCG5/ABCG8 in heterozygosity that can cause hypercholesterolemia and should be further investigated. This extended next-generation sequencing panel identifies individuals with FH and FH-phenocopies, allowing to personalize each person's treatment according to the affected pathway.

A fast linkage method for population GWAS cohorts with related individuals.

Linkage analysis, a class of methods for detecting co-segregation of genomic segments and traits in families, was used to map disease-causing genes for decades before genotyping arrays and dense SNP genotyping enabled genome-wide association studies in population samples. Population samples often contain related individuals, but the segregation of alleles within families is rarely used because traditional linkage methods are computationally inefficient for larger datasets. Here, we describe Population Linkage, a novel application of Haseman-Elston regression as a method of moments estimator of variance components and their standard errors. We achieve additional computational efficiency by using modern methods for detection of IBD segments and variance component estimation, efficient preprocessing of input data, and minimizing redundant numerical calculations. We also refined variance component models to account for the biases in population-scale methods for IBD segment detection. We ran Population Linkage on four blood lipid traits in over 70,000 individuals from the HUNT and SardiNIA studies, successfully detecting 25 known genetic signals. One notable linkage signal that appeared in both was for low-density lipoprotein (LDL) cholesterol levels in the region near the gene APOE (LOD = 29.3, variance explained = 4.1%). This is the region where the missense variants rs7412 and rs429358, which together make up the ε2, ε3, and ε4 alleles each account for 2.4% and 0.8% of variation in circulating LDL cholesterol. Our results show the potential for linkage analysis and other large-scale applications of method of moments variance components estimation.

Efficacy and Safety of an Investigational Single-Course CRISPR Base-Editing Therapy Targeting PCSK9 in Nonhuman Primate and Mouse Models.

BACKGROUND: VERVE-101 is an investigational in vivo CRISPR base-editing medicine designed to alter a single DNA base in the PCSK9 gene, permanently turn off hepatic protein production, and thereby durably lower low-density lipoprotein cholesterol. We test the efficacy, durability, tolerability, and potential for germline editing of VERVE-101 in studies of nonhuman primates and a murine F1 progeny study. METHODS: Cynomolgus monkeys were given a single intravenous infusion of a vehicle control (n=10) or VERVE-101 at a dose of 0.75 mg/kg (n=4) or 1.5 mg/kg (n=22) with subsequent follow-up up to 476 days. Two studies assessed the potential for germline editing, including sequencing sperm samples from sexually mature male nonhuman primates treated with VERVE-101 and genotyping offspring from female mice treated with the murine surrogate of VERVE-101 (VERVE-101mu). RESULTS: Liver biopsies 14 days after dosing noted mean PCSK9 editing of 46% and 70% in monkeys treated with VERVE-101 at 0.75 and 1.5 mg/kg, respectively. This translated into mean reductions in blood PCSK9 (proprotein convertase subtilisin/kexin type 9) of 67% and 83% and reductions of low-density lipoprotein cholesterol of 49% and 69% at the 0.75 and 1.5 mg/kg doses, respectively, assessed as time-weighted average change from baseline between day 28 and up to 476 days after dosing. Liver safety monitoring noted a transient rise in alanine aminotransferase and aspartate aminotransferase concentrations after infusion that fully resolved by day 14 with no accompanying change in total bilirubin. In a subset of monkeys necropsied 1 year after dosing, no findings related to VERVE-101 were identified on macroscopic and histopathologic assessment of the liver and other organs. In the study to assess potential germline editing of male nonhuman primates, sperm samples collected after VERVE-101 dosing showed no evidence of PCSK9 editing. Among 436 offspring of female mice treated with a saturating dose of VERVE-101mu, the PCSK9 edit was transmitted in 0 of 436 animals. CONCLUSIONS: VERVE-101 was well tolerated in nonhuman primates and led to 83% lower blood PCSK9 protein and 69% lower low-density lipoprotein cholesterol with durable effects up to 476 days after dosing. These results have supported the initiation of a first-in-human clinical trial in patients with heterozygous familial hypercholesterolemia and atherosclerotic cardiovascular disease.

Meta-GWAS of PCSK9 levels detects two novel loci at APOB and TM6SF2.

BACKGROUND: Proprotein convertase subtilisin/kexin type 9 (PCSK9) is a key player in lipid metabolism, as it degrades low-density lipoprotein (LDL) receptors from hepatic cell membranes. So far, only variants of the PCSK9 gene locus were found to be associated with PCSK9 levels. Here we aimed to identify novel genetic loci that regulate PCSK9 levels and how they relate to other lipid traits. Additionally, we investigated to what extend the causal effect of PCSK9 on coronary artery disease (CAD) is mediated by low-density lipoprotein-cholesterol (LDL-C). METHODS AND RESULTS: We performed a genome-wide association study meta-analysis of PCSK9 levels in up to 12 721 samples of European ancestry. The estimated heritability was 10.3%, which increased to 12.6% using only samples from patients without statin treatment. We successfully replicated the known PCSK9 hit consisting of three independent signals. Interestingly, in a study of 300 African Americans, we confirmed the locus with a different PCSK9 variant. Beyond PCSK9, our meta-analysis detected three novel loci with genome-wide significance. Co-localization analysis with cis-eQTLs and lipid traits revealed biologically plausible candidate genes at two of them: APOB and TM6SF2. In a bivariate Mendelian Randomization analysis, we detected a strong effect of PCSK9 on LDL-C, but not vice versa. LDL-C mediated 63% of the total causal effect of PCSK9 on CAD. CONCLUSION: Our study identified novel genetic loci with plausible candidate genes affecting PCSK9 levels. Ethnic heterogeneity was observed at the PCSK9 locus itself. Although the causal effect of PCSK9 on CAD is mainly mediated by LDL-C, an independent direct effect also occurs.

Causal role of lipid metabolism in pulmonary alveolar proteinosis: an observational and mendelian randomisation study.

BACKGROUND: Pulmonary alveolar proteinosis (PAP) is a rare interstitial lung disease characterised by the accumulation of lipoprotein material in the alveoli. Although dyslipidaemia is a prominet feature, the causal effect of lipid traits on PAP remains unclear. This study aimed to explore the role of lipid traits in PAP and evaluate the potential of lipid-lowering drug targets in PAP. METHODS: Clinical outcomes, lipid profiles and lung function tests were analysed in a clinical cohort of diagnosed PAP patients and propensity score-matched healthy controls. Genome-wide association study data on PAP, lipid metabolism, blood cells and variants of genes encoding potential lipid-lowering drug targets were obtained for Mendelian randomisation (MR) and mediation analyses. FINDINGS: Observational results showed that higher levels of total cholesterol (TC), triglycerides and low-density lipoprotein (LDL) were associated with increased risks of PAP. Higher levels of TC and LDL were also associated with worse PAP severity. In MR analysis, elevated LDL was associated with an increased risk of PAP (OR: 4.32, 95% CI: 1.63 to 11.61, p=0.018). Elevated monocytes were associated with a lower risk of PAP (OR 0.34, 95% CI: 0.18 to 0.66, p=0.002) and mediated the risk impact of LDL on PAP. Genetic mimicry of PCSK9 inhibition was associated with a reduced risk of PAP (OR 0.03, p=0.007). INTERPRETATION: Our results support the crucial role of lipid and metabolism-related traits in PAP risk, emphasising the monocyte-mediated, causal effect of elevated LDL in PAP genetics. PCSK9 mediates the development of PAP by raising LDL. These finding provide evidence for lipid-related mechanisms and promising lipid-lowering drug target for PAP.

Haplotype analysis and linkage disequilibrium of ApoB gene polymorphisms and its relationship with hyperlipidemia in patients with acne vulgaris.

BACKGROUND: Acne vulgaris (AV) is a chronic, multifactorial inflammatory disease of the pilosebaceous unit brought on by hormonal imbalance, excessive sebum production, follicular hyperkeratinization, inflammation and Cutibacterium acne. Acne patients are characterized by alteration of the lipid profile. Apolipoprotein B gene (ApoB) plays an essential role in lipoprotein biosynthesis and multiple single-nucleotide polymorphisms (SNPs) in ApoB are associated with dyslipidemia. AIM: The aim of this study was to estimate the alteration of lipid profiles in AV, determine the genetic association with lipid profile alteration by studying the ApoB gene polymorphisms, and to identify the exact haplotypes associated with acne and lipid profile alteration. SUBJECTS AND METHODS: In a case-control study consisting of 63 non-obese acne patients and 43 healthy controls, all participants underwent biochemical, anthropological assessments, and genetic analysis for ApoB polymorphisms. RESULT: Our results indicate that serum ApoB and the lipid profile were higher in acne patients compared with healthy subject. The most common haplotypes in acne patients were rs562338 A/rs17240441 I/c.12669 A/rs1042034 G, whereas the most common haplotypes in healthy subjects were rs562338 G/rs17240441 D/c.12669 A/rs1042034 G. Patients with mild acne had higher serum ApoB levels p = 0.005. Also, the low-density lipoprotein cholesterol (LDL-C) level was higher in mild acne compared with other acne groups, with a highly significant variation of p ≤ 0.001. CONCLUSION: We found a significant variation between the acne group and healthy controls in serum ApoB, triglycerides, total cholesterol and LDL-C. The most common haplotypes in acne patients are rs562338 A/, rs17240441 I/, c.12669 A/ and rs1042034 G, and there is a linkage disequilibrium between the four selected SNPs.

Genetic identification of familial hypercholesterolemia within whole genome sequences in 6820 newborns.

Familial hypercholesterolemia (FH) is defined as a monogenic disease, characterized by elevated low-density lipoprotein cholesterol (LDL-C) levels. FH remains underdiagnosed and undertreated in Chinese. We whole-genome sequenced 6820 newborns from Qingdao of China to investigate the FH-related gene (LDLR, APOB, PCSK9) mutation types, carrier ratio and genotype-phenotype correlation. In this study, the prevalence of FH in Qingdao of China was 0.47% (95% CI: 0.32%-0.66%). The plasma lipid levels of FH-related gene mutation carriers begin to increase as early as infant. T-CHO and LDL-C of FH infants was higher by 48.1% (p < 0.001) and 42.9% (p < 0.001) relative to non-FH infants. A total of 22 FH infants and their parent participate in further studies. The results indicated that FH infant parent noncarriers have the normal plasma lipid level, while T-CHO and LDL-C increased in FH infants and FH infant parent carriers, but no difference between the groups. This highlights the importance of genetic factors. In conclusion, the spectrum of FH-causing mutations in the newborns of Qingdao, China was described for the first time. These data can serve as a considerable dataset for next-generation sequencing analysis of the Chinese population with FH and potentially helping reform regional policies for early detection and prevention of FH.

Genetic backgrounds and diagnosis of familial hypercholesterolemia.

Lipid disorders play a critical role in the intricate development of atherosclerosis and its clinical consequences, such as coronary heart disease and stroke. These disorders are responsible for a significant number of deaths in many adult populations worldwide. Familial hypercholesterolemia (FH) is a genetic disorder that causes extremely high levels of LDL cholesterol. The most common mutations occur in genes responsible for low-density lipoprotein receptor (LDLR), apolipoprotein B (APOB), or proprotein convertase subtilisin/kexin type 9 (PCSK9). While genetic testing is a dependable method for diagnosing the disease, it may not detect primary mutations in 20%-40% of FH cases.

Lipid Metabolism, Methylation Aberrant, and Osteoporosis: A Multi-omics Study Based on Mendelian Randomization.

BACKGROUND: Observational studies have shown a causal association between dyslipidemia and osteoporosis, but the genetic causation and complete mechanism of which are uncertain. The disadvantage of previous observational studies is that they are susceptible to confounding factors and bias, that makes it difficult to infer a causal link between those two diseases. Abnormal epigenetic modifications, represented by DNA methylation, are important causes of many diseases. However, there are no studies showing a bridging role for methylation modifications in blood lipid metabolism and osteoporosis. METHODS: SNPs for lipid profile (Blood VLDL cholesterol (VLDL-C), blood LDL cholesterol (LDL-C), blood HDL cholesterol (HDL-C), blood triglycerides (TG), diagnosed pure hypercholesterolaemia, blood apolipoprotein B (Apo B), blood apolipoprotein A1(Apo A1)), and bone mineral density (BMD) in different body parts (Heel BMD, lumbar BMD, whole-body BMD, femoral neck BMD) were obtained from large meta-analyses of genome-wide association studies as instrumental variables for two-sample Mendelian randomization. Assessment of the genetic effects of lipid profile-associated methylation sites and bone mineral density was carried out using the summary-data-based Mendelian randomization (SMR) method. RESULTS: Two-sample Mendelian randomization showed that there was a negative causal association between hypercholesterolaemia and heel BMD (p = 0.0103, OR = 0.4590), and total body BMD (p = 0.0002, OR = 0.2826). LDL-C had a negative causal association with heel BMD (p = 8.68E-05, OR = 0.9586). VLDL-C had a negative causal association with heel BMD (p = 0.035, OR = 0.9484), lumbar BMD (p = 0.0316, OR = 0.9356), and total body BMD (p = 0.0035, OR = 0.9484). HDL-C had a negative causal association with heel BMD (p = 1.25E-05, OR = 0.9548), lumbar BMD (p = 0.0129, OR = 0.9358), and total body BMD (p = 0.0399, OR = 0.9644). Apo B had a negative causal association with heel BMD (p = 0.0001, OR = 0.9647). Apo A1 had a negative causal association with heel BMD (p = 0.0132, OR = 0.9746) and lumbar BMD (p = 0.0058, OR = 0.9261). The p-values of all positive results corrected by the FDR method remained significant and sensitivity analysis showed that there was no horizontal pleiotropy in the results despite the heterogeneity in some results. SMR identified 3 methylation sites associated with lipid profiles in the presence of genetic effects on BMD: cg15707428(GREB1), cg16000331(SREBF2), cg14364472(NOTCH1). CONCLUSION: Our study provides insights into the potential causal links and co-pathogenesis between dyslipidemia and osteoporosis. The genetic effects of dyslipidaemia on osteoporosis may be related to certain aberrant methylation genetic modifications.

Blood Lipid Metabolic Profiles and Causal Links to Site-Specific Cancer Risks: A Mendelian Randomization Study.

Observational and Mendelian randomization (MR) studies have established links between dyslipidemia and select cancer susceptibilities. However, there is a lack of comprehensive exploration of causal relationships spanning diverse cancer types. Here, we conducted a two-sample MR analysis to elucidate the causative connections between 9 blood lipid metabolic profiles (namely, adiponectin, leptin, lipoprotein A, apolipoprotein A1, apolipoprotein B, cholesterol, triglycerides, LDL-cholesterol, and HDL-cholesterol) and 21 site-specific cancer risks. Our findings reveal genetically predicted adiponectin levels to be associated with a reduced ovarian cancer risk, while genetically determined leptin increases bladder cancer risk but decreases prostate cancer risk. Lipoprotein A elevates risk of prostate cancer while diminishing risk of endometrial cancer, while apolipoprotein A1 heightens risks of breast and cervical cancers. Furthermore, elevated levels of cholesterol are positively correlated with kidney cancer, and triglycerides demonstrate a positive association with non-melanoma skin cancer but a negative association with breast cancer. Protective effects of genetically predicted LDL-cholesterol on endometrial cancer and adverse effects of HDL-cholesterol on breast cancer are also observed. Our study conclusively establishes that blood lipid metabolic profiles exert causal effects on cancer susceptibility, providing more robust evidence for cancer prevention and prompting contemplation regarding the future health of the human populace.

A regulatory element associated to NAFLD in the promoter of DIO1 controls LDL-C, HDL-C and triglycerides in hepatic cells.

BACKGROUND: Genome-wide association studies (GWAS) have identified genetic variants linked to fat metabolism and related traits, but rarely pinpoint causative variants. This limitation arises from GWAS not considering functional implications of noncoding variants that can affect transcription factor binding and potentially regulate gene expression. The aim of this study is to investigate a candidate noncoding functional variant within a genetic locus flagged by a GWAS SNP associated with non-alcoholic fatty liver disease (NAFLD), a condition characterized by liver fat accumulation in non-alcohol consumers. METHODS: CRISPR-Cas9 gene editing in HepG2 cells was used to modify the regulatory element containing the candidate functional variant linked to NAFLD. Global gene expression in mutant cells was assessed through RT-qPCR and targeted transcriptomics. A phenotypic assay measured lipid droplet accumulation in the CRISPR-Cas9 mutants. RESULTS: The candidate functional variant, rs2294510, closely linked to the NAFLD-associated GWAS SNP rs11206226, resided in a regulatory element within the DIO1 gene's promoter region. Altering this element resulted in changes in transcription factor binding sites and differential expression of candidate target genes like DIO1, TMEM59, DHCR24, and LDLRAD1, potentially influencing the NAFLD phenotype. Mutant HepG2 cells exhibited increased lipid accumulation, a hallmark of NAFLD, along with reduced LDL-C, HDL-C and elevated triglycerides. CONCLUSIONS: This comprehensive approach, that combines genome editing, transcriptomics, and phenotypic assays identified the DIO1 promoter region as a potential enhancer. Its activity could regulate multiple genes involved in the NAFLD phenotype or contribute to defining a polygenic risk score for enhanced risk assessment in NAFLD patients.

Novel loci linked to serum lipid traits are identified in a genome-wide association study of a highly admixed Brazilian population - the 2015 ISA Nutrition.

BACKGROUND: Cardiovascular diseases (CVDs) comprise major causes of death worldwide, leading to extensive burden on populations and societies. Alterations in normal lipid profiles, i.e., dyslipidemia, comprise important risk factors for CVDs. However, there is lack of comprehensive evidence on the genetic contribution to dyslipidemia in highly admixed populations. The identification of single nucleotide polymorphisms (SNPs) linked to blood lipid traits in the Brazilian population was based on genome-wide associations using data from the São Paulo Health Survey with Focus on Nutrition (ISA-Nutrition). METHODS: A total of 667 unrelated individuals had genetic information on 330,656 SNPs available, and were genotyped with Axiom™ 2.0 Precision Medicine Research Array. Genetic associations were tested at the 10- 5 significance level for the following phenotypes: low-density lipoprotein cholesterol (LDL-c), very low-density lipoprotein cholesterol (VLDL-c), high-density lipoprotein cholesterol (HDL-c), HDL-c/LDL-c ratio, triglycerides (TGL), total cholesterol, and non-HDL-c. RESULTS: There were 19 significantly different SNPs associated with lipid traits, the majority of which corresponding to intron variants, especially in the genes FAM81A, ZFHX3, PTPRD, and POMC. Three variants (rs1562012, rs16972039, and rs73401081) and two variants (rs8025871 and rs2161683) were associated with two and three phenotypes, respectively. Among the subtypes, non-HDL-c had the highest proportion of associated variants. CONCLUSIONS: The results of the present genome-wide association study offer new insights into the genetic structure underlying lipid traits in underrepresented populations with high ancestry admixture. The associations were robust across multiple lipid phenotypes, and some of the phenotypes were associated with two or three variants. In addition, some variants were present in genes that encode ncRNAs, raising important questions regarding their role in lipid metabolism.

Associations of ACE I/D and AGTR1 rs5182 polymorphisms with diabetes and their effects on lipids in an elderly Chinese population.

BACKGROUND: Diabetes mellitus is generally accompanied by dyslipidaemia, but inconsistent relationships between lipid profiles and diabetes are noted. Moreover, genetic variations in insertion/deletion (I/D) polymorphisms at angiotensin-converting enzyme gene (ACE) and T/C polymorphisms in the angiotensin type 1 receptor gene (AGTR1) are related to diabetes and lipid levels, but the associations are controversial. Thus, the current research aimed to explore the effects of ACE I/D, AGTR1 rs5182 and diabetes mellitus on serum lipid profiles in 385 Chinese participants with an average age of 75.01 years. METHODS: The ACE I/D variant was identified using the polymerase chain reaction (PCR) method, whereas the AGTR1 rs5182 polymorphism was identified using the PCR-based restriction fragment length polymorphism (PCR-RFLP) method and verified with DNA sequencing. Total cholesterol (TC), triglyceride (TG), apolipoprotein A (ApoA), apolipoprotein B (ApoB), high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C) levels were measured using routine methods, and the lipid ratios were calculated. RESULTS: ACE I/D, but not AGTR1 rs5182, was a predictor of TG/HDL-C for the whole study population. Both ACE I/D and AGTR1 rs5182 were predictors of HDL-C and LDL-C levels in females but not in males. Moreover, in females, diabetes mellitus and ACE I/D were identified as predictors of TG and TG/HDL-C, whereas AGTR1 rs5182 and diabetes mellitus were predictors of TG/HDL-C. Moreover, diabetes mellitus and the combination of ACE I/D and AGTR1 rs5182 variations were predictors of TG and TG/HDL-C exclusively in females. CONCLUSIONS: The results demonstrated the potential for gender-dependent interactions of ACE I/D, AGTR1 rs5182, and diabetes on lipid profiles. These findings may serve as an additional explanation for the inconsistent changes of blood lipids in individuals with diabetes mellitus, thereby offering a novel perspective for the clinical management of blood lipid levels in diabetic patients.