GWAS in Africans identifies novel lipids loci and demonstrates heterogenous association within Africa

AbstractBackgroundSerum lipids are biomarkers of cardiometabolic disease risk, and understanding the genomic factors contributing to their distribution has been of considerable interest. Large genome-wide association studies (GWAS) have identified over 150 lipids loci; however, GWAS of Africans (AF) are rare. Given the genomic diversity among those of African ancestry, it is expected that a GWAS in Africans could identify novel lipids loci. While GWAS have been conducted in African Americans (AA), such studies are not proxies for studies in continental Africans due to the drastically different environmental context. Therefore, we conducted a GWAS of 4,317 Africans enrolled in the Africa America Diabetes Mellitus study.Methods and ResultsWe used linear mixed models of the inverse normal transformations of covariate-djusted residuals of high-density lipoprotein cholesterol (HDLC), low-density lipoprotein cholesterol (LDLC), total cholesterol (CHOL), triglycerides (TG), and TG/HDLC, with adjustment for three principal components and the random effect of relatedness. Replication of loci associated at p<5×10−8 was attempted in 9,542 AA. Meta-analysis of AF and AA was also conducted. We also conducted analyses that excluded the relatively small number of East Africans. We evaluated known lipids loci in Africans using both exact replication and “local” replication, which accounts for interethnic differences in linkage disequilibrium.In our main analysis, we identified 23 novel associations in Africans. Of the 14 of these that were able to be tested in AA, two associations replicated (GPNMB-TG and ENPP1-TG). Two additional novel loci were discovered upon meta-analysis with AA (rs138282551-TG and TLL2-CHOL). Analyses considering only those with predominantly West African ancestry (Nigeria, Ghana, and AA) yielded new insights: ORC5-LDLC and chr20:60973327-CHOL.ConclusionsWhile functional work will be useful to confirm and understand the biological mechanisms underlying these associations, this study demonstrates the utility of conducting large-scale genomic analyses in Africans for discovering novel loci. The functional significance of some of these loci in relation to lipids remains to be elucidated, yet some have known connections to lipids pathways. For instance, rs147706369 (intronic, TLL2) alters a regulatory motif for sterol regulatory element-binding proteins (SREBPs), which are a family of transcription factors that control the expression of a range of enzymes involved in cholesterol, fatty acid, and triglyceride synthesis.

Download Full-text

Capturing SNP Association across the NK Receptor and HLA Gene Regions in Multiple Sclerosis by Targeted Penalised Regression Models

Genes ◽

10.3390/genes13010087 ◽

2021 ◽

Vol 13 (1) ◽

pp. 87

Author(s):

Sean M. Burnard ◽

Rodney A. Lea ◽

Miles Benton ◽

David Eccles ◽

Daniel W. Kennedy ◽

...

Keyword(s):

Multiple Sclerosis ◽

Complex Traits ◽

Multiple Testing ◽

Large Scale ◽

Disease Risk ◽

Association Studies ◽

Meta Analysis ◽

Elastic Net ◽

Genome Wide Association Studies ◽

Multiple Testing Correction

Conventional genome-wide association studies (GWASs) of complex traits, such as Multiple Sclerosis (MS), are reliant on per-SNP p-values and are therefore heavily burdened by multiple testing correction. Thus, in order to detect more subtle alterations, ever increasing sample sizes are required, while ignoring potentially valuable information that is readily available in existing datasets. To overcome this, we used penalised regression incorporating elastic net with a stability selection method by iterative subsampling to detect the potential interaction of loci with MS risk. Through re-analysis of the ANZgene dataset (1617 cases and 1988 controls) and an IMSGC dataset as a replication cohort (1313 cases and 1458 controls), we identified new association signals for MS predisposition, including SNPs above and below conventional significance thresholds while targeting two natural killer receptor loci and the well-established HLA loci. For example, rs2844482 (98.1% iterations), otherwise ignored by conventional statistics (p = 0.673) in the same dataset, was independently strongly associated with MS in another GWAS that required more than 40 times the number of cases (~45 K). Further comparison of our hits to those present in a large-scale meta-analysis, confirmed that the majority of SNPs identified by the elastic net model reached conventional statistical GWAS thresholds (p < 5 × 10−8) in this much larger dataset. Moreover, we found that gene variants involved in oxidative stress, in addition to innate immunity, were associated with MS. Overall, this study highlights the benefit of using more advanced statistical methods to (re-)analyse subtle genetic variation among loci that have a biological basis for their contribution to disease risk.

Download Full-text

Abstract 141: APOA1, CETP, and CILP2 Variants Modify the Lipid Response to Fenofibrate: Genetics of Lipid Lowering and Diet Network

Arteriosclerosis Thrombosis and Vascular Biology ◽

10.1161/atvb.32.suppl_1.a141 ◽

2012 ◽

Vol 32 (suppl_1) ◽

Author(s):

Stella Aslibekyan ◽

Marguerite M Irvin ◽

Alexis C Frazier-Wood ◽

Robert J Straka ◽

Ingrid B Borecki ◽

...

Keyword(s):

Blood Lipids ◽

Association Studies ◽

Meta Analysis ◽

Density Lipoprotein ◽

Lipoprotein Cholesterol ◽

Lipid Lowering ◽

Genome Wide Association Studies ◽

Genome Wide ◽

Lipid Response ◽

Induced Changes

Introduction: Despite the widespread use of fibrates in treatment of dyslipidemia, the observed response is highly heterogeneous, suggesting a role for genetic determinants. Whether replicated variants associated with blood lipids identified by genome wide association studies (GWAS) are also associated with lipid response to fenofibrate is unknown. Objectives: To test if 95 genome-wide significant loci identified in a recent meta-analysis of blood lipids are associated with changes in high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), non-HDL-C, and triglycerides (TG) following 3 weeks of therapy with 160 mg of micronized fenofibrate. Methods: Using data from 861 European American Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) participants, we fit mixed linear models with baseline blood lipids and the post-to-pre fenofibrate treatment ratio of blood lipid levels as outcomes, the corresponding genetic markers from the published meta-analysis as predictors, and age, sex, pedigree, and ancestry as assessed by principal components as covariates. A Bonferroni correction was applied to adjust for multiple comparisons. Least square means were used to report the direction of fenofibrate-induced changes by genotype. Results: We observed statistically significant associations between rs964184 , a variant near the APOA1 gene, and baseline HDL-C (P<0.0001) and baseline TG (P<0.0001), as well as with diminished response to fenofibrate as evidenced by a smaller increase in HDL-C (P<0.0001) and a smaller decrease in TG (P=0.0001) per each copy of the variant allele. Additionally, we report suggestive associations of rs3764261 locus in the CETP gene and the rs10401969 locus in the CILP2 gene with decreased fenofibrate response as measured by changes in LDL-C (P=0.0003 and 0.02, respectively) and non-HDL-C (P=0.004 and 0.005, respectively). Conclusions: We have identified several novel biologically relevant loci associated with baseline blood lipids and fenofibrate-induced changes in blood lipids.

Download Full-text

Abstract 051: Trans-ethnic Metabochip Genotyping of Established Lipid Loci Identifies Low Frequency Susceptibility Variants and Additional Independent Signals in Known Loci

Circulation ◽

10.1161/circ.125.suppl_10.a051 ◽

2012 ◽

Vol 125 (suppl_10) ◽

Author(s):

Ying Wu ◽

Steven Buyske ◽

Themistocles Assimes ◽

Linda S Adair ◽

Christie Ballantyne ◽

...

Keyword(s):

Association Studies ◽

Large Fraction ◽

African Ancestry ◽

Low Frequency ◽

Density Lipoprotein ◽

High Density ◽

Lipoprotein Cholesterol ◽

Genome Wide Association Studies ◽

Nutrition Survey ◽

Functional Variants

Genome-wide association studies (GWAS) have identified ∼100 loci for triglycerides (TG), high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C), but much of the trait heritability remains unexplained. We conducted a trans-ethnic study in 5,884 African Americans (AA) in the Population Architecture using Genomics and Epidemiology (PAGE) consortium [the Atherosclerosis Risk in Communities Study (ARIC), the Multiethnic Cohort Study (MEC) and the Women's Health Initiative (WHI)], and 1,719 East Asians (ASN) from the Cebu Longitudinal Health and Nutrition Survey (CLHNS) to analyze high-density genotyped Metabochip SNPs for association with TG, HDL-C and LDL-C. We aimed to identify population-specific and additional independent signals at established lipid loci and to assess the relative evidence of association with SNPs previously reported to have a functional effect. Among the 58 lipid loci tested, evidence of association (P<10–4) was observed in at least one of the populations for 21 loci, including 19 loci in AA and 7 loci in ASN. Using sequential conditional analysis, we detected in AA that the LDL-C locus PCSK9 harbored five independent nonsense or non-synonymous variants (C679X, A443T, N425S, Y142X and L253F). All had low frequency (MAF: 0.004–0.095), were unique to AA (MAF=0 in non-African ancestry populations) and have been reported previously to affect protein function. These five SNPs collectively explained 2.9% of the LDL-C variability compared to 1.1% explained by C679X alone. Similarly, the APOE-C1 cluster revealed two AA-specific TG signals represented by rs12721054 (APOC1 3'UTR, MAF=0.12) and rs769455 (APOE R163C, MAF=0.002, prior evidence of biological function) that together accounted for 1.7% of the total TG variation compared to the 1.0% explained by the strongest APOE-C1 SNP alone. At a third locus, TG-associated APOA5, two reportedly functional variants, S19W (MAF=0.059) and −3A>G (MAF=0.26), exhibited the strongest association in AA and ASN, respectively. In AA, three independent signals at APOA5 explained 1.7% of the TG variation; in ASN, two independent signals explained 3.3% of total variation. The reportedly functional variants were included or well-represented on Metabochip at ten loci. At eight of the ten loci, the reported variants (at 6 loci) or proxies (r2>.95, at 2 loci) showed the strongest association in at least one population. This study highlights the value of the trans-ethnic high-density genotyping to identify a wider spectrum of susceptibility variants at reported loci, both additional independent signals and population-specific SNP effects, that more than double the trait variation explained. In addition, the large fraction of reportedly functional SNPs that showed the strongest evidence of association suggests that lead SNPs at novel loci frequently may be good candidates for functional studies.

Download Full-text

Causal Evaluation of Laboratory Markers in Type 2 Diabetes on Cancer and Vascular Diseases Using Various Mendelian Randomization Tools

Frontiers in Genetics ◽

10.3389/fgene.2020.597420 ◽

2020 ◽

Vol 11 ◽

Author(s):

Heejin Jin ◽

Sanghun Lee ◽

Sungho Won

Keyword(s):

Type 2 Diabetes ◽

Large Scale ◽

Mendelian Randomization ◽

Association Studies ◽

Meta Analysis ◽

Density Lipoprotein ◽

Postprandial Glucose ◽

Genome Wide Association Studies ◽

Weighted Median

Multiple studies have demonstrated the effects of type 2 diabetes (T2D) on various human diseases; however, most of these were observational epidemiological studies that suffered from many potential biases including reported confounding and reverse causations. In this article, we investigated whether cancer and vascular disease can be affected by T2D-related traits, including fasting plasma glucose (FPG), 2-h postprandial glucose (2h-PG), and glycated hemoglobin A1c (HbA1c) levels, by using Mendelian randomization (MR). The summary statistics for FPG, 2h-PG, and HbA1c level were obtained through meta-analyses of large-scale genome-wide association studies that included data from 133,010 nondiabetic individuals from collaborating Meta-analysis of Glucose and Insulin Related Traits Consortium studies. Thereafter, based on the statistical assumptions for MR analyses, the most reliable approaches including inverse-variance-weighted (IVW), MR-Egger, MR-Egger with a simulation extrapolation (SIMEX), weighted median, and MR-pleiotropy residual sum and outlier (MR-PRESSO) methods were applied to identify traits affected by FPG, 2h-PG, and HbAlc. We found that coronary artery disease is affected by FPG, as per the IVW [log odds ratio (logOR): 0.21; P = 0.012], MR-Egger (SIMEX) (logOR: 0.22; P = 0.014), MR-PRESSO (logOR: 0.18; P = 0.045), and weighted median (logOR: 0.29; P < 0.001) methods but not as per the MR-Egger (logOR: 0.13; P = 0.426) approach. Furthermore, low-density lipoprotein cholesterol levels are affected by HbA1c, as per the IVW [beta (B): 0.23; P = 0.015), MR-Egger (B: 0.45; P = 0.046), MR-Egger (SIMEX) (B: 0.27; P = 0.007), MR-PRESSO (B; 0.14; P = 0.010), and the weighted median (B: 0.15; P = 0.012] methods. Further studies of the associated biological mechanisms are required to validate and understand the disease-specific differences identified in the TD2-related causal effects of each trait.

Download Full-text

Trans-Ethnic Meta-Analysis of Interactions Between Genetics and Early-Life Socioeconomic Context on Memory Performance and Decline in Older Americans

The Journals of Gerontology Series A ◽

10.1093/gerona/glab255 ◽

2021 ◽

Author(s):

Jessica D Faul ◽

Minjung Kho ◽

Wei Zhao ◽

Kalee E Rumfelt ◽

Miao Yu ◽

...

Keyword(s):

Parental Education ◽

Association Studies ◽

Memory Performance ◽

Meta Analysis ◽

African Ancestry ◽

Later Life ◽

European Ancestry ◽

Genome Wide Association Studies ◽

Multiple Testing Correction ◽

Socioeconomic Context

Abstract Background Later-life cognitive function is influenced by genetics as well as early- and later-life socioeconomic context. However, few studies have examined the interaction between genetics and early childhood factors. Methods Using gene-based tests (interaction sequence kernel association test [iSKAT]/iSKAT optimal unified test), we examined whether common and/or rare exonic variants in 39 gene regions previously associated with cognitive performance, dementia, and related traits had an interaction with childhood socioeconomic context (parental education and financial strain) on memory performance or decline in European ancestry (EA, N = 10 468) and African ancestry (AA, N = 2 252) participants from the Health and Retirement Study. Results Of the 39 genes, 22 in EA and 19 in AA had nominally significant interactions with at least one childhood socioeconomic measure on memory performance and/or decline; however, all but one (father’s education by solute carrier family 24 member 4 [SLC24A4] in AA) were not significant after multiple testing correction (false discovery rate [FDR] < .05). In trans-ethnic meta-analysis, 2 genes interacted with childhood socioeconomic context (FDR < .05): mother’s education by membrane-spanning 4-domains A4A (MS4A4A) on memory performance, and father’s education by SLC24A4 on memory decline. Both interactions remained significant (p < .05) after adjusting for respondent’s own educational attainment, apolipoprotein-ε4 allele (APOE ε4) status, lifestyle factors, body mass index, and comorbidities. For both interactions in EA and AA, the genetic effect was stronger in participants with low parental education. Conclusions Examination of common and rare variants in genes discovered through genome-wide association studies shows that childhood context may interact with key gene regions to jointly impact later-life memory function and decline. Genetic effects may be more salient for those with lower childhood socioeconomic status.

Download Full-text

Abstract 367: Extreme High-Density Lipoprotein Cholesterol Genetics: An Assortment of Large and Small Polygenic Effects

Arteriosclerosis Thrombosis and Vascular Biology ◽

10.1161/atvb.37.suppl_1.367 ◽

2017 ◽

Vol 37 (suppl_1) ◽

Author(s):

Jacqueline S Dron ◽

Jian Wang ◽

Cécile Low-Kam ◽

Sumeet A Khetarpal ◽

John F Robinson ◽

...

Keyword(s):

Large Scale ◽

Genetic Basis ◽

Rare Variants ◽

Association Studies ◽

Density Lipoprotein ◽

Copy Number Variations ◽

Genome Wide Association Studies ◽

Common Variants ◽

Targeted Next Generation Sequencing ◽

Common Genetic Variants

Rationale: Although HDL-C levels are known to have a complex genetic basis, most studies have focused solely on identifying rare variants with large phenotypic effects to explain extreme HDL-C phenotypes. Objective: Here we concurrently evaluate the contribution of both rare and common genetic variants, as well as large-scale copy number variations (CNVs), towards extreme HDL-C concentrations. Methods: In clinically ascertained patients with low ( N =136) and high ( N =119) HDL-C profiles, we applied our targeted next-generation sequencing panel (LipidSeq TM ) to sequence genes involved in HDL metabolism, which were subsequently screened for rare variants and CNVs. We also developed a novel polygenic trait score (PTS) to assess patients’ genetic accumulations of common variants that have been shown by genome-wide association studies to associate primarily with HDL-C levels. Two additional cohorts of patients with extremely low and high HDL-C (total N =1,746 and N =1,139, respectively) were used for PTS validation. Results: In the discovery cohort, 32.4% of low HDL-C patients carried rare variants or CNVs in primary ( ABCA1 , APOA1 , LCAT ) and secondary ( LPL , LMF1 , GPD1 , APOE ) HDL-C–altering genes. Additionally, 13.4% of high HDL-C patients carried rare variants or CNVs in primary ( SCARB1 , CETP , LIPC , LIPG ) and secondary ( APOC3 , ANGPTL4 ) HDL-C–altering genes. For polygenic effects, patients with abnormal HDL-C profiles but without rare variants or CNVs were ~2-fold more likely to have an extreme PTS compared to normolipidemic individuals, indicating an increased frequency of common HDL-C–associated variants in these patients. Similar results in the two validation cohorts demonstrate that this novel PTS successfully quantifies common variant accumulation, further characterizing the polygenic basis for extreme HDL-C phenotypes. Conclusions: Patients with extreme HDL-C levels have various combinations of rare variants, common variants, or CNVs driving their phenotypes. Fully characterizing the genetic basis of HDL-C levels must extend to encompass multiple types of genetic determinants—not just rare variants—to further our understanding of this complex, controversial quantitative trait.

Download Full-text

A Review of the Hereditary Component of Triple Negative Breast Cancer: High- and Moderate-Penetrance Breast Cancer Genes, Low-Penetrance Loci, and the Role of Nontraditional Genetic Elements

Journal of Oncology ◽

10.1155/2019/4382606 ◽

2019 ◽

Vol 2019 ◽

pp. 1-10 ◽

Cited By ~ 11

Author(s):

Darrell L. Ellsworth ◽

Clesson E. Turner ◽

Rachel E. Ellsworth

Keyword(s):

Breast Cancer ◽

Triple Negative Breast Cancer ◽

Large Scale ◽

Triple Negative ◽

Association Studies ◽

African Ancestry ◽

Genome Wide Association Studies ◽

Genetic Elements ◽

Genome Wide ◽

Increased Risk

Triple negative breast cancer (TNBC), representing 10-15% of breast tumors diagnosed each year, is a clinically defined subtype of breast cancer associated with poor prognosis. The higher incidence of TNBC in certain populations such as young women and/or women of African ancestry and a unique pathological phenotype shared between TNBC and BRCA1-deficient tumors suggest that TNBC may be inherited through germline mutations. In this article, we describe genes and genetic elements, beyond BRCA1 and BRCA2, which have been associated with increased risk of TNBC. Multigene panel testing has identified high- and moderate-penetrance cancer predisposition genes associated with increased risk for TNBC. Development of large-scale genome-wide SNP assays coupled with genome-wide association studies (GWAS) has led to the discovery of low-penetrance TNBC-associated loci. Next-generation sequencing has identified variants in noncoding RNAs, viral integration sites, and genes in underexplored regions of the human genome that may contribute to the genetic underpinnings of TNBC. Advances in our understanding of the genetics of TNBC are driving improvements in risk assessment and patient management.

Download Full-text

Comment on ‘Large-Scale Cognitive GWAS Meta-Analysis Reveals Tissue-Specific Neural Expression and Potential Nootropic Drug Targets’ by Lam et al.

Twin Research and Human Genetics ◽

10.1017/thg.2018.12 ◽

2018 ◽

Vol 21 (2) ◽

pp. 84-88 ◽

Cited By ~ 6

Author(s):

W. David Hill

Keyword(s):

Genetic Information ◽

Drug Targets ◽

Large Scale ◽

Association Studies ◽

Meta Analysis ◽

Genetic Correlations ◽

Data Sets ◽

Genome Wide Association Studies ◽

Nootropic Drug ◽

Genome Wide

Intelligence and educational attainment are strongly genetically correlated. This relationship can be exploited by Multi-Trait Analysis of GWAS (MTAG) to add power to Genome-wide Association Studies (GWAS) of intelligence. MTAG allows the user to meta-analyze GWASs of different phenotypes, based on their genetic correlations, to identify association's specific to the trait of choice. An MTAG analysis using GWAS data sets on intelligence and education was conducted by Lam et al. (2017). Lam et al. (2017) reported 70 loci that they described as ‘trait specific’ to intelligence. This article examines whether the analysis conducted by Lam et al. (2017) has resulted in genetic information about a phenotype that is more similar to education than intelligence.

Download Full-text

Human demographic history impacts genetic risk prediction across diverse populations

10.1101/070797 ◽

2016 ◽

Cited By ~ 7

Author(s):

Alicia R. Martin ◽

Christopher R. Gignoux ◽

Raymond K. Walters ◽

Genevieve L. Wojcik ◽

Benjamin M. Neale ◽

...

Keyword(s):

Risk Prediction ◽

Large Scale ◽

Disease Risk ◽

Association Studies ◽

Demographic History ◽

Population History ◽

Risk Scores ◽

Genome Wide Association Studies ◽

Summary Statistics ◽

Medical Genomics

AbstractThe vast majority of genome-wide association studies are performed in Europeans, and their transferability to other populations is dependent on many factors (e.g. linkage disequilibrium, allele frequencies, genetic architecture). As medical genomics studies become increasingly large and diverse, gaining insights into population history and consequently the transferability of disease risk measurement is critical. Here, we disentangle recent population history in the widely-used 1000 Genomes Project reference panel, with an emphasis on populations underrepresented in medical studies. To examine the transferability of single-ancestry GWAS, we used published summary statistics to calculate polygenic risk scores for six well-studied traits and diseases. We identified directional inconsistencies in all scores; for example, height is predicted to decrease with genetic distance from Europeans, despite robust anthropological evidence that West Africans are as tall as Europeans on average. To gain deeper quantitative insights into GWAS transferability, we developed a complex trait coalescent-based simulation framework considering effects of polygenicity, causal allele frequency divergence, and heritability. As expected, correlations between true and inferred risk were typically highest in the population from which summary statistics were derived. We demonstrated that scores inferred from European GWAS were biased by genetic drift in other populations even when choosing the same causal variants, and that biases in any direction were possible and unpredictable. This work cautions that summarizing findings from large-scale GWAS may have limited portability to other populations using standard approaches, and highlights the need for generalized risk prediction methods and the inclusion of more diverse individuals in medical genomics.

Download Full-text

The effects of L-carnitine supplementation on lipid concentrations inpatients with type 2 diabetes: A systematic review and meta-analysis of randomized clinical trials

Journal of Cardiovascular and Thoracic Research ◽

10.34172/jcvtr.2020.43 ◽

2020 ◽

Vol 12 (4) ◽

pp. 246-255

Author(s):

Omid Asbaghi ◽

Sara Kashkooli ◽

Mohammad Reza Amini ◽

Hossein Shahinfar ◽

Kurosh Djafarian ◽

...

Keyword(s):

Clinical Trials ◽

Lipid Profile ◽

Baseline Level ◽

Randomized Clinical Trials ◽

Meta Analysis ◽

Random Effect ◽

Random Effect Model ◽

Density Lipoprotein ◽

Lipoprotein Cholesterol ◽

Carnitine Supplementation

This meta-analysis was performed to assess the effect of L-carnitine supplementation on lipid profile. A systematic search were conducted in PubMed and Scopus to identify randomized clinical trials (RCTs) which evaluated the effects of L-carnitine on lipid profile. Pooled effect sizes were measured using random-effect model (Dersimonian-Laird). Meta-analysis showed that L-carnitine supplementation significantly reduced total cholesterol (TC) (weighted mean difference [WMD]: -8.17 mg/dL; 95% CI,-14.68 to -1.65, I2=52.2%, P = 0.041). Baseline level of TC was a source of heterogeneity, with a greater effect in studies with a baseline level of more than 200 mg/d (WMD: -11.93 mg/dL; 95% CI, -20.80 to-3.05). L-carnitine also significantly decreased low-density lipoprotein-cholesterol (LDL-C) (WMD:-5.22 mg/dL; 95% CI, -9.54 to -0.91, I2=66.7%, P = 0.010), and LDL-C level <100 mg/dL), trial duration,and L-carnitine dosage were potential sources of heterogeneity. L-carnitine supplementation appeared to have no significant effect on high-density lipoprotein-cholesterol (HDL-C) (WMD: -0.51 mg/dL;95% CI, -2.45 to 1.44) and triglyceride (TG) (WMD: 2.80 mg/dL; 95% CI, -8.09 to 13.69). This meta-analysisrevealed that L-carnitine may have favorable effects on lipid profile, especially LDL-C and TC. However, further RCTs are needed to confirm the veracity of these results, particularly among hyperlipidemic patients.

Download Full-text