Assessing efficiency of fine-mapping obesity-associated variants through leveraging ancestry architecture and functional annotation using PAGE and UKBB cohorts.

Inadequate representation of non-European ancestry populations in genome-wide association studies (GWAS) has limited opportunities to isolate functional variants. Fine-mapping in multi-ancestry populations should improve the efficiency of prioritizing variants for functional interrogation. To evaluate this hypothesis, we leveraged ancestry architecture to perform comparative GWAS and fine-mapping of obesity-related phenotypes in European ancestry populations from the UK Biobank (UKBB) and multi-ancestry samples from the Population Architecture for Genetic Epidemiology (PAGE) consortium with comparable sample sizes. In the investigated regions with genome-wide significant associations for obesity-related traits, fine-mapping in our ancestrally diverse sample led to 95% and 99% credible sets (CS) with fewer variants than in the European ancestry sample. Lead fine-mapped variants in PAGE regions had higher average coding scores, and higher average posterior probabilities for causality compared to UKBB. Importantly, 99% CS in PAGE loci contained strong expression quantitative trait loci (eQTLs) in adipose tissues or harbored more variants in tighter linkage disequilibrium (LD) with eQTLs. Leveraging ancestrally diverse populations with heterogeneous ancestry architectures, coupled with functional annotation, increased fine-mapping efficiency and performance, and reduced the set of candidate variants for consideration for future functional studies. Significant overlap in genetic causal variants across populations suggests generalizability of genetic mechanisms underpinning obesity-related traits across populations.

Association between pain intensity and depressive symptoms in community-dwelling adults: longitudinal findings from the Survey of Health, Ageing and Retirement in Europe (SHARE).

PURPOSE: To investigate the longitudinal associations between pain and depressive symptoms in adults. METHODS: Prospective cohort study on data from 28,515 community-dwelling adults ≥ 50 years, free from depression at baseline (Wave 5), with follow-up in Wave 6 of the Survey of Health, Ageing and Retirement in Europe (SHARE). Significant depressive symptoms were defined by a EURO-D score ≥ 4. The longitudinal association between baseline pain intensity and significant depressive symptoms at follow-up was analysed using logistic regression models; odds ratios (ORs) and confidence intervals (CI) were calculated, adjusting for socio-demographic and clinical factors, physical inactivity, loneliness, mobility and functional impairments. RESULTS: Mean age was 65.4 years (standard deviation 9.0, range 50-99); 14,360 (50.4%) participants were women. Mean follow-up was 23.4 (standard deviation 3.4) months. At baseline, 2803 (9.8%) participants reported mild pain, 5253 (18.4%) moderate pain and 1431 (5.0%) severe pain. At follow-up, 3868 (13.6%) participants-1451 (10.3%) men and 2417 (16.8%) women-reported significant depressive symptoms. After adjustment, mild, moderate and severe baseline pain, versus no pain, were associated with an increased likelihood of significant depressive symptoms at follow-up: ORs (95% CI) were 1.20 (1.06-1.35), 1.32 (1.20-1.46) and 1.39 (1.19-1.63), respectively. These associations were more pronounced in men compared to women, and consistent in participants aged 50-64 years, those without mobility or functional impairment, and those without loneliness at baseline. CONCLUSION: Higher baseline pain intensity was longitudinally associated with a greater risk of significant depressive symptoms at 2-year follow-up, in community-dwelling adults without baseline depression.

Effect of tissue-grouped regulatory variants associated to type 2 diabetes in related secondary outcomes.

Genome-wide association studies have identified over five hundred loci that contribute to variation in type 2 diabetes (T2D), an established risk factor for many diseases. However, the mechanisms and extent through which these loci contribute to subsequent outcomes remain elusive. We hypothesized that combinations of T2D-associated variants acting on tissue-specific regulatory elements might account for greater risk for tissue-specific outcomes, leading to diversity in T2D disease progression. We searched for T2D-associated variants acting on regulatory elements and expression quantitative trait loci (eQTLs) in nine tissues. We used T2D tissue-grouped variant sets as genetic instruments to conduct 2-Sample Mendelian Randomization (MR) in ten related outcomes whose risk is increased by T2D using the FinnGen cohort. We performed PheWAS analysis to investigate whether the T2D tissue-grouped variant sets had specific predicted disease signatures. We identified an average of 176 variants acting in nine tissues implicated in T2D, and an average of 30 variants acting on regulatory elements that are unique to the nine tissues of interest. In 2-Sample MR analyses, all subsets of regulatory variants acting in different tissues were associated with increased risk of the ten secondary outcomes studied on similar levels. No tissue-grouped variant set was associated with an outcome significantly more than other tissue-grouped variant sets. We did not identify different disease progression profiles based on tissue-specific regulatory and transcriptome information. Bigger sample sizes and other layers of regulatory information in critical tissues may help identify subsets of T2D variants that are implicated in certain secondary outcomes, uncovering system-specific disease progression.

The association between leptin and subclinical cardiovascular disease explained by body fat: Observational and Mendelian randomization analyses.

BACKGROUND AND AIMS: Leptin has been associated with adverse effects on cardiovascular disease, but the effect of confounding by body fat in these associations remains unclear. To investigate associations between leptin and heart function and subclinical cardiovascular disease adjusted for total body fat, and to investigate the causal relation between leptin and cardiovascular disease using Mendelian randomisation. METHODS AND RESULTS: Leptin concentrations, total body fat and diverse measures of subclinical cardiovascular disease were determined in participants of the Netherlands Epidemiology of Obesity study. Linear regression between leptin concentration and measures of heart function, ECG measures, and carotid intima media thickness as a measure of subclinical atherosclerosis was adjusted for potential confounding factors, and additionally including total body fat. We analysed the combined effects of genetic variants from a GWAS on leptin concentrations in publicly-available summary statistics of coronary heart disease GWAS (CARDIoGRAMplusC4D, n = 184,305). As many as 6107 men and women, mean (SD) age 56 (6) years, BMI 26 (4) kg/m2, and median leptin concentration 12.1 µg (IQR: 6.7-22.6) were included. In observational analyses, leptin was weakly associated with heart function and subclinical cardiovascular disease, but these associations attenuated when adjusting for total body fat. A doubling of genetically-determined leptin concentration was associated with an odds ratio of cardiovascular disease of 0.69 (0.37, 1.27). CONCLUSION: Observational associations between leptin and subclinical measures of cardiovascular disease were largely explained by differences in total body fat. Results of analyses of genetically-determined leptin and coronary heart disease risk were inconclusive due to a large confidence interval.

The contribution of functional HNF1A variants and polygenic susceptibility to risk of type 2 diabetes in ancestrally diverse populations.

AIMS/HYPOTHESIS: We examined the contribution of rare HNF1A variants to type 2 diabetes risk and age of diagnosis, and the extent to which their impact is affected by overall genetic susceptibility, across three ancestry groups. METHODS: Using exome sequencing data of 160,615 individuals of the UK Biobank and 18,797 individuals of the BioMe Biobank, we identified 746 carriers of rare functional HNF1A variants (minor allele frequency ≤1%), of which 507 carry variants in the functional domains. We calculated polygenic risk scores (PRSs) based on genome-wide association study summary statistics for type 2 diabetes, and examined the association of HNF1A variants and PRS with risk of type 2 diabetes and age of diagnosis. We also tested whether the PRS affects the association between HNF1A variants and type 2 diabetes risk by including an interaction term. RESULTS: Rare HNF1A variants that are predicted to impair protein function are associated with increased risk of type 2 diabetes in individuals of European ancestry (OR 1.46, p=0.049), particularly when the variants are located in the functional domains (OR 1.89, p=0.002). No association was observed for individuals of African ancestry (OR 1.10, p=0.60) or Hispanic-Latino ancestry (OR 1.00, p=1.00). Rare functional HNF1A variants were associated with an earlier age at diagnosis in the Hispanic-Latino population (ß=-5.0 years, p=0.03), and this association was marginally more pronounced for variants in the functional domains (ß=-5.59 years, p=0.03). No associations were observed for other ancestries (African ancestry ß=-2.7 years, p=0.13; European ancestry ß=-3.5 years, p=0.20). A higher PRS was associated with increased odds of type 2 diabetes in all ancestries (OR 1.61-2.11, p<10-5) and an earlier age at diagnosis in individuals of African ancestry (ß=-1.4 years, p=3.7 × 10-6) and Hispanic-Latino ancestry (ß=-2.4 years, p<2 × 10-16). Furthermore, a higher PRS exacerbated the effect of the functional HNF1A variants on type 2 diabetes in the European ancestry population (pinteraction=0.037). CONCLUSIONS/INTERPRETATION: We show that rare functional HNF1A variants, in particular those located in the functional domains, increase the risk of type 2 diabetes, at least among individuals of European ancestry. Their effect is even more pronounced in individuals with a high polygenic susceptibility. Our analyses highlight the importance of the location of functional variants within a gene and an individual's overall polygenic susceptibility, and emphasise the need for more genetic data in non-European populations.

Erratum: Ancestral diversity improves discovery and fine-mapping of genetic loci for anthropometric traits-The Hispanic/Latino Anthropometry Consortium.

[This corrects the article DOI: 10.1016/j.xhgg.2022.100099.].

A multi-ethnic polygenic risk score is associated with hypertension prevalence and progression throughout adulthood.

In a multi-stage analysis of 52,436 individuals aged 17-90 across diverse cohorts and biobanks, we train, test, and evaluate a polygenic risk score (PRS) for hypertension risk and progression. The PRS is trained using genome-wide association studies (GWAS) for systolic, diastolic blood pressure, and hypertension, respectively. For each trait, PRS is selected by optimizing the coefficient of variation (CV) across estimated effect sizes from multiple potential PRS using the same GWAS, after which the 3 trait-specific PRSs are combined via an unweighted sum called "PRSsum", forming the HTN-PRS. The HTN-PRS is associated with both prevalent and incident hypertension at 4-6 years of follow up. This association is further confirmed in age-stratified analysis. In an independent biobank of 40,201 individuals, the HTN-PRS is confirmed to be predictive of increased risk for coronary artery disease, ischemic stroke, type 2 diabetes, and chronic kidney disease.

Ancestral diversity improves discovery and fine-mapping of genetic loci for anthropometric traits-The Hispanic/Latino Anthropometry Consortium.

Hispanic/Latinos have been underrepresented in genome-wide association studies (GWAS) for anthropometric traits despite their notable anthropometric variability, ancestry proportions, and high burden of growth stunting and overweight/obesity. To address this knowledge gap, we analyzed densely imputed genetic data in a sample of Hispanic/Latino adults to identify and fine-map genetic variants associated with body mass index (BMI), height, and BMI-adjusted waist-to-hip ratio (WHRadjBMI). We conducted a GWAS of 18 studies/consortia as part of the Hispanic/Latino Anthropometry (HISLA) Consortium (stage 1, n = 59,771) and generalized our findings in 9 additional studies (stage 2, n = 10,538). We conducted a trans-ancestral GWAS with summary statistics from HISLA stage 1 and existing consortia of European and African ancestries. In our HISLA stage 1 + 2 analyses, we discovered one BMI locus, as well as two BMI signals and another height signal each within established anthropometric loci. In our trans-ancestral meta-analysis, we discovered three BMI loci, one height locus, and one WHRadjBMI locus. We also identified 3 secondary signals for BMI, 28 for height, and 2 for WHRadjBMI in established loci. We show that 336 known BMI, 1,177 known height, and 143 known WHRadjBMI (combined) SNPs demonstrated suggestive transferability (nominal significance and effect estimate directional consistency) in Hispanic/Latino adults. Of these, 36 BMI, 124 height, and 11 WHRadjBMI SNPs were significant after trait-specific Bonferroni correction. Trans-ancestral meta-analysis of the three ancestries showed a small-to-moderate impact of uncorrected population stratification on the resulting effect size estimates. Our findings demonstrate that future studies may also benefit from leveraging diverse ancestries and differences in linkage disequilibrium patterns to discover novel loci and additional signals with less residual population stratification.

Stratification of Type 2 Diabetes by Age of Diagnosis in the UK Biobank Reveals Subgroup-Specific Genetic Associations and Causal Risk Profiles.

The pathogenesis of type 2 diabetes (T2D) might change with increasing age. Here, we used a stratification based on age of diagnosis to gain insight into the genetics and causal risk factors of T2D across different age-groups. We performed genome-wide association studies (GWAS) on T2D and T2D subgroups based on age of diagnosis (<50, 50-60, 60-70, and >70 years) (total of 24,986 cases). As control subjects, participants were at least 70 years of age at the end of follow-up without developing T2D (N =187,130). GWAS identified 208 independent lead single nucleotide polymorphism (SNPs) mapping to 69 loci associated with T2D (P < 1.0e-8). Among others, SNPs mapped to CDKN2B-AS1 and multiple independent SNPs mapped to TCF7L2 were more strongly associated with cases diagnosed after age 70 years than with cases diagnosed before age 50 years. Based on the different case groups, we performed two-sample Mendelian randomization. Most notably, we observed that of the investigated risk factors, the association between BMI and T2D attenuated with increasing age of diagnosis. Collectively, our results indicate that stratification of T2D based on age of diag-nosis reveals subgroup-specific genetics and causal determinants, supporting the hypothesis that the pathogenesis of T2D changes with increasing age.

The Pharmacogenetics of Statin Therapy on Clinical Events: No Evidence that Genetic Variation Affects Statin Response on Myocardial Infarction.

Background: The pharmacogenetic effect on cardiovascular disease reduction in response to statin treatment has only been assessed in small studies. In a pharmacogenetic genome wide association study (GWAS) analysis within the Genomic Investigation of Statin Therapy (GIST) consortium, we investigated whether genetic variation was associated with the response of statins on cardiovascular disease risk reduction. Methods: The investigated endpoint was incident myocardial infarction (MI) defined as coronary heart disease death and definite and suspect non-fatal MI. For imputed single nucleotide polymorphisms (SNPs), regression analysis was performed on expected allelic dosage and meta-analysed with a fixed-effects model, inverse variance weighted meta-analysis. All SNPs with p-values <5.0 × 10-4 in stage 1 GWAS meta-analysis were selected for further investigation in stage-2. As a secondary analysis, we extracted SNPs from the Stage-1 GWAS meta-analysis results based on predefined hypotheses to possibly modifying the effect of statin therapy on MI. Results: In stage-1 meta-analysis (eight studies, n = 10,769, 4,212 cases), we observed no genome-wide significant results (p < 5.0 × 10-8). A total of 144 genetic variants were followed-up in the second stage (three studies, n = 1,525, 180 cases). In the combined meta-analysis, no genome-wide significant hits were identified. Moreover, none of the look-ups of SNPs known to be associated with either CHD or with statin response to cholesterol levels reached Bonferroni level of significance within our stage-1 meta-analysis. Conclusion: This GWAS analysis did not provide evidence that genetic variation affects statin response on cardiovascular risk reduction. It does not appear likely that genetic testing for predicting effects of statins on clinical events will become a useful tool in clinical practice.

The contribution of tissue-grouped BMI-associated gene sets to cardiometabolic-disease risk: a Mendelian randomization study.

BACKGROUND: Body mass index (BMI)-associated loci are used to explore the effects of obesity using Mendelian randomization (MR), but the contribution of individual tissues to risks remains unknown. We aimed to identify tissue-grouped pathways of BMI-associated loci and relate these to cardiometabolic disease using MR analyses. METHODS: Using Genotype-Tissue Expression (GTEx) data, we performed overrepresentation tests to identify tissue-grouped gene sets based on mRNA-expression profiles from 634 previously published BMI-associated loci. We conducted two-sample MR with inverse-variance-weighted methods, to examine associations between tissue-grouped BMI-associated genetic instruments and type 2 diabetes mellitus (T2DM) and coronary artery disease (CAD), with use of summary-level data from published genome-wide association studies (T2DM: 74 124 cases, 824 006 controls; CAD: 60 801 cases, 123 504 controls). Additionally, we performed MR analyses on T2DM and CAD using randomly sampled sets of 100 or 200 BMI-associated genetic variants. RESULTS: We identified 17 partly overlapping tissue-grouped gene sets, of which 12 were brain areas, where BMI-associated genes were differentially expressed. In tissue-grouped MR analyses, all gene sets were similarly associated with increased risks of T2DM and CAD. MR analyses with randomly sampled genetic variants on T2DM and CAD resulted in a distribution of effect estimates similar to tissue-grouped gene sets. CONCLUSIONS: Overrepresentation tests revealed differential expression of BMI-associated genes in 17 different tissues. However, with our biology-based approach using tissue-grouped MR analyses, we did not identify different risks of T2DM or CAD for the BMI-associated gene sets, which was reflected by similar effect estimates obtained by randomly sampled gene sets.

Association of High-Density Lipoprotein Cholesterol With Cognitive Function: Findings From the PROspective Study of Pravastatin in the Elderly at Risk.

Objective: We aimed to examine whether variability in high-density lipoprotein cholesterol (HDL-c) over time was associated with cognitive function. Method: We conducted a post hoc analysis of the PROspective Study of Pravastatin in the Elderly at Risk (PROSPER) trial. Our sample included 4,428 participants with at least two repeated HDL-c measures between Months 3 and 24 postbaseline and with cognitive assessments at Month 30. HDL-c variability was defined as the intraindividual standard deviation over each person's repeated measurements. Results: Higher HDL-c variability was associated with worse performance on the Letter-Digit Coding Test (ß [95% confidence interval] [CI] = -4.39 [-7.36, -1.43], p = .004), immediate recall on the 15-Picture Learning Test (ß [95% CI] = -0.98 [-1.86, -0.11], p = .027), and delayed recall on the 15-Picture Learning Test (ß [95% CI] = -1.90 [-3.14, -0.67], p = .002). The associations did not vary by treatment group. Discussion: Our findings suggest that variability in HDL-c may be associated with poor cognitive function among older adults.

The Separate Contributions of Visceral Fat and Liver Fat to Chronic Kidney Disease-Related Renal Outcomes.

OBJECTIVES: This study aims to investigate the separate contributions of liver fat and visceral fat on microalbuminuria and impaired renal function, and second, to examine whether non-alcoholic fatty liver disease is causally related to microalbuminuria and/or impaired renal function. METHODS: Associations between visceral adipose tissue (VAT), hepatic triglyceride content (HTGC), and risk of microalbuminuria and renal function were studied cross-sectionally in the Netherlands Epidemiology of Obesity study. Mendelian randomization using GWAS meta-analysis data was performed to estimate the causal effect of non-alcoholic fatty liver disease (PNPLA3, LYPLAL1, NCAN, GCKR) on eGFR (Nmax 118,460), microalbuminuria (Nmax 54,116), and impaired renal function (Nmax 118,147). RESULTS: In total, 2,023 participants (mean age 55.5 ± 6.0 years, 53% women) were included of which 29% had fatty liver and 2.0% chronic kidney disease stage ≥3. In joint models, VAT was associated with a 2-fold increased risk of microalbuminuria which was mainly driven by the association in women (total population: per standard deviation [SD] = 55.4 cm2, odds ratio [OR] 2.02, 95% confidence interval [CI] 1.18-3.47; women: OR 2.83, 95% CI 1.44, 5.56), but HTGC was not (total population: per SD = 7.9%, OR 1.20, 95% CI 0.85, 1.70). No associations were found for VAT and HTGC with eGFR (VAT: per SD = 55.4 cm2, OR 1.25, 95% CI 0.83, 1.87; HTGC: per SD = 7.9%, OR 0.65, 95% CI 0.42, 0.99). No causal effect of NAFLD on microalbuminuria or impaired renal function was found. CONCLUSIONS: In observational analyses, visceral fat was associated with microalbuminuria in women. Liver fat was not associated with microalbuminuria or renal function, which was supported by Mendelian randomization. Visceral fat might be more important than liver fat in the etiology of microalbuminuria.

Statin-induced LDL cholesterol response and type 2 diabetes: a bidirectional two-sample Mendelian randomization study.

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, nmax = 40,914) and DIAGRAM (nmax = 159,208) consortia, we found a positive genetic correlation between LDL-C statin response and T2D using LD score regression (rgenetic = 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.

Survival Bias in Mendelian Randomization Studies: A Threat to Causal Inference.

It has been argued that survival bias may distort results in Mendelian randomization studies in older populations. Through simulations of a simple causal structure we investigate the degree to which instrumental variable (IV)-estimators may become biased in the context of exposures that affect survival. We observed that selecting on survival decreased instrument strength and, for exposures with directionally concordant effects on survival (and outcome), introduced downward bias of the IV-estimator when the exposures reduced the probability of survival till study inclusion. Higher ages at study inclusion generally increased this bias, particularly when the true causal effect was not equal to null. Moreover, the bias in the estimated exposure-outcome relation depended on whether the estimation was conducted in the one- or two-sample setting. Finally, we briefly discuss which statistical approaches might help to alleviate this and other types of selection bias. See video abstract at, http://links.lww.com/EDE/B589.

Low Birth Weight and Kidney Function in Middle-Aged Men and Women: The Netherlands Epidemiology of Obesity Study.

RATIONALE & OBJECTIVE: Chronic kidney disease (CKD), defined as estimated glomerular filtration rate (eGFR)<60mL/min/1.73m2, is a risk factor for cardiovascular morbidity and mortality. Little is known about low birth weight and risk for CKD in middle-aged adults in the general population. We estimated the causal association between birth weight and eGFR in a Dutch cohort of middle-aged men and women. STUDY DESIGN: Retrospective cohort study. SETTING & PARTICIPANTS: 6,671 participants in the Netherlands Epidemiology of Obesity (NEO) Study. Replication study using data for 133,814 participants studied by the CKDGen consortium. EXPOSURE: Birth weight was self-reported and also based on an instrumental variable, 59 birth weight-associated genetic variants, derived from an independent data source. OUTCOME: eGFR at the age of 45 to 65 years. ANALYTICAL APPROACH: We assessed the association between self-reported birth weight and eGFR in the NEO Study using multivariable linear regression, adjusted for age, sex, education, smoking, and alcohol use. The effect of the instrument on eGFR was estimated using separate 2-sample Mendelian randomization analyses: one using individual data from the NEO cohort and one using summary data from the CKDGen consortium. RESULTS: At baseline, mean eGFR was 86±12.4 (SD) mL/min/1.73m2. After multivariable adjustment, self-reported birth weight was not associated with kidney function in middle age. Two-sample Mendelian randomization analysis showed that in the NEO cohort, for each 500-g lower birth weight defined using genetic variants, there was a 3.7 (95% CI, 0.5-6.9)-mL/min/1.73m2 lower eGFR at the age of 45 to 65 years. However, using CKDGen summary-level data, there was a smaller nonsignificant relationship between birth weight and eGFR. LIMITATIONS: Birth weight was self-reported. CONCLUSIONS: Lower birth weight defined using genetic variants was associated with lower eGFRs in Dutch middle-aged adults. However, this finding was not replicated within the CKDGen consortium.

Metabolomics Profiling of Visceral Adipose Tissue: Results From MESA and the NEO Study.

Background Identifying associations between serum metabolites and visceral adipose tissue ( VAT ) could provide novel biomarkers of VAT and insights into the pathogenesis of obesity-related diseases. We aimed to discover and replicate metabolites reflecting pathways related to VAT . Methods and Results Associations between fasting serum metabolites and VAT area (by computed tomography or magnetic resonance imaging) were assessed with cross-sectional linear regression of individual-level data from participants in MESA (Multi-Ethnic Study of Atherosclerosis; discovery, N=1103) and the NEO (Netherlands Epidemiology of Obesity) study (replication, N=2537). Untargeted 1H nuclear magnetic resonance metabolomics profiling of serum was performed in MESA, and metabolites were replicated in the NEO study using targeted 1H nuclear magnetic resonance spectroscopy. A total of 30 590 metabolomic spectral variables were evaluated. After adjustment for age, sex, race/ethnicity, socioeconomic status, smoking, physical activity, glucose/lipid-lowering medication, and body mass index, 2104 variables representing 24 nonlipid and 49 lipid/lipoprotein subclass metabolites remained significantly associated with VAT ( P=4.88×10-20-1.16×10-3). These included conventional metabolites, amino acids, acetylglycoproteins, intermediates of glucose and hepatic metabolism, organic acids, and subclasses of apolipoproteins, cholesterol, phospholipids, and triglycerides. Metabolites mapped to 31 biochemical pathways, including amino acid substrate use/metabolism and glycolysis/gluconeogenesis. In the replication cohort, acetylglycoproteins, branched-chain amino acids, lactate, glutamine (inversely), and atherogenic lipids remained associated with VAT ( P=1.90×10-35-8.46×10-7), with most associations remaining after additional adjustment for surrogates of VAT (glucose level, waist circumference, and serum triglycerides), reflecting novel independent associations. Conclusions We identified and replicated a metabolite panel associated with VAT in 2 community-based cohorts. These findings persisted after adjustment for body mass index and appear to define a metabolic signature of visceral adiposity.

Visit-to-visit lipid variability: Clinical significance, effects of lipid-lowering treatment, and (pharmaco) genetics.

In recent years, visit-to-visit variability of serum lipids has been linked to both clinical outcomes and surrogate markers for vascular disease. In this article, we present an overview of the current evidence connecting this intraindividual variability to these outcome measures, discuss its interplay with lipid-lowering treatment, and describe the literature regarding genetic factors of possible interest. In addition, we undertook an explorative genome-wide association analysis on visit-to-visit variability of low-density lipoprotein cholesterol and high-density lipoprotein cholesterol, examining additive effects in 2530 participants from the placebo arm of the PROspective Study of Pravastatin in the Elderly at Risk trial. While we identified suggestive associations (P < 1 × 10-6) at 3 different loci (KIAA0391, amiloride-sensitive cation channel 1 neuronal [ACCN1], and Dickkopf WNT signaling pathway inhibitor 3 [DKK3]), previously published data from the genome-wide association study literature did not suggest plausible mechanistic pathways. Given the large degree of both clinical and methodological heterogeneity in the literature, additional research is needed to harmonize visit-to-visit variability parameters across studies and to definitively assess the possible role of (pharmaco)genetic factors.

Relations between lipoprotein(a) concentrations, LPA genetic variants, and the risk of mortality in patients with established coronary heart disease: a molecular and genetic association study.

BACKGROUND: Lipoprotein(a) concentrations in plasma are associated with cardiovascular risk in the general population. Whether lipoprotein(a) concentrations or LPA genetic variants predict long-term mortality in patients with established coronary heart disease remains less clear. METHODS: We obtained data from 3313 patients with established coronary heart disease in the Ludwigshafen Risk and Cardiovascular Health (LURIC) study. We tested associations of tertiles of lipoprotein(a) concentration in plasma and two LPA single-nucleotide polymorphisms ([SNPs] rs10455872 and rs3798220) with all-cause mortality and cardiovascular mortality by Cox regression analysis and with severity of disease by generalised linear modelling, with and without adjustment for age, sex, diabetes diagnosis, systolic blood pressure, BMI, smoking status, estimated glomerular filtration rate, LDL-cholesterol concentration, and use of lipid-lowering therapy. Results for plasma lipoprotein(a) concentrations were validated in five independent studies involving 10 195 patients with established coronary heart disease. Results for genetic associations were replicated through large-scale collaborative analysis in the GENIUS-CHD consortium, comprising 106 353 patients with established coronary heart disease and 19 332 deaths in 22 studies or cohorts. FINDINGS: The median follow-up was 9·9 years. Increased severity of coronary heart disease was associated with lipoprotein(a) concentrations in plasma in the highest tertile (adjusted hazard radio [HR] 1·44, 95% CI 1·14-1·83) and the presence of either LPA SNP (1·88, 1·40-2·53). No associations were found in LURIC with all-cause mortality (highest tertile of lipoprotein(a) concentration in plasma 0·95, 0·81-1·11 and either LPA SNP 1·10, 0·92-1·31) or cardiovascular mortality (0·99, 0·81-1·2 and 1·13, 0·90-1·40, respectively) or in the validation studies. INTERPRETATION: In patients with prevalent coronary heart disease, lipoprotein(a) concentrations and genetic variants showed no associations with mortality. We conclude that these variables are not useful risk factors to measure to predict progression to death after coronary heart disease is established. FUNDING: Seventh Framework Programme for Research and Technical Development (AtheroRemo and RiskyCAD), INTERREG IV Oberrhein Programme, Deutsche Nierenstiftung, Else-Kroener Fresenius Foundation, Deutsche Stiftung für Herzforschung, Deutsche Forschungsgemeinschaft, Saarland University, German Federal Ministry of Education and Research, Willy Robert Pitzer Foundation, and Waldburg-Zeil Clinics Isny.