Background: Parkinson's disease (PD) is a common neurodegenerative disorder, characterized by a clinical symptomatology involving both motor and non-motor symptoms. Motor complications associated with long-term dopaminergic treatment include motor fluctuations and levodopa-induced dyskinesia (LID), which may have a major impact on the quality of life. The clinical features and onset time of motor complications in the disease course are heterogeneous, and the etiology remains unknown. Objective: We aimed to identify genomic variants associated with the development of motor fluctuations and LID at 5 years after the onset of PD. Methods: Genomic data were obtained using Affymetrix Axiom KORV1.1 array, including an imputation genome-wide association study (GWAS) grid and other GWAS loci; functional variants of the non-synonymous exome; pharmacogenetic variants; variants in genes involved in absorption, distribution, metabolism, and excretion of drugs; and expression quantitative trait loci in 741 patients with PD. Results: FAM129B single-nucleotide polymorphism (SNP) rs10760490 was nominally associated with the occurrence of motor fluctuations at 5 years after the onset of PD [odds ratio (OR) = 2.9, 95% confidence interval (CI) = 1.8-4.8, P = 6.5 × 10-6]. GALNT14 SNP rs144125291 was significantly associated with the occurrence of LID (OR = 5.5, 95% CI = 2.9-10.3, P = 7.88 × 10-9) and was still significant after Bonferroni correction. Several other genetic variants were associated with the occurrence of motor fluctuations or LID, but the associations were not significant after Bonferroni correction. Conclusion: This study identified new loci associated with the occurrence of motor fluctuations and LID at 5 years after the onset of PD. However, further studies are needed to confirm our findings.
Motor fluctuations in levodopa treated Parkinson's disease
Levodopa-induced dyskinesia in levodopa treated Parkinson's disease
OBJECTIVE: Dysregulation of type I collagen metabolism has a great impact on human health. We have previously seen that matrix metalloproteinase-degraded type I collagen (C1M) is associated with early death and age-related pathologies. To dissect the biological impact of type I collagen dysregulation, we have performed a genome-wide screening of the genetic factors related to type I collagen turnover. METHODS: Patient registry data and genotypes have been collected for a total of 4,981 Danish postmenopausal women. Genome-wide association with serum levels of C1M was assessed and phenotype-genotype association analysis performed. RESULTS: Twenty-two genome-wide significant variants associated with C1M were identified in the APOE-C1/TOMM40 gene cluster. The APOE-C1/TOMM40 gene cluster is associated with hyperlipidemia and cognitive disorders, and we further found that C1M levels correlated with tau degradation markers and were decreased in women with preclinical cognitive impairment. CONCLUSIONS: Our study provides elements for better understanding the role of the collagen metabolism in the onset of cognitive impairment.
BACKGROUND: Biological aging estimators derived from DNA methylation data are heritable and correlate with morbidity and mortality. Consequently, identification of genetic and environmental contributors to the variation in these measures in populations has become a major goal in the field. RESULTS: Leveraging DNA methylation and SNP data from more than 40,000 individuals, we identify 137 genome-wide significant loci, of which 113 are novel, from genome-wide association study (GWAS) meta-analyses of four epigenetic clocks and epigenetic surrogate markers for granulocyte proportions and plasminogen activator inhibitor 1 levels, respectively. We find evidence for shared genetic loci associated with the Horvath clock and expression of transcripts encoding genes linked to lipid metabolism and immune function. Notably, these loci are independent of those reported to regulate DNA methylation levels at constituent clock CpGs. A polygenic score for GrimAge acceleration showed strong associations with adiposity-related traits, educational attainment, parental longevity, and C-reactive protein levels. CONCLUSION: This study illuminates the genetic architecture underlying epigenetic aging and its shared genetic contributions with lifestyle factors and longevity.
DNA methylation Hannum age acceleration
DNA methylation GrimAge acceleration
Intrinsic epigenetic age acceleration
DNA methylation PhenoAge acceleration
DNA methylation-estimated plasminogen activator inhibitor-1 levels
BACKGROUND: Currently, diabetes has become one of the leading causes of death worldwide. Fasting plasma glucose (FPG) levels that are higher than optimal, even if below the diagnostic threshold of diabetes, can also lead to increased morbidity and mortality. Here we intend to study the magnitude of the genetic influence on FPG variation by conducting structural equation modelling analysis and to further identify specific genetic variants potentially related to FPG levels by performing a genome-wide association study (GWAS) in Chinese twins. RESULTS: The final sample included 382 twin pairs: 139 dizygotic (DZ) pairs and 243 monozygotic (MZ) pairs. The DZ twin correlation for the FPG level (rDZ = 0.20, 95% CI: 0.04-0.36) was much lower than half that of the MZ twin correlation (rMZ = 0.68, 95% CI: 0.62-0.74). For the variation in FPG level, the AE model was the better fitting model, with additive genetic parameters (A) accounting for 67.66% (95% CI: 60.50-73.62%) and unique environmental or residual parameters (E) accounting for 32.34% (95% CI: 26.38-39.55%), respectively. In the GWAS, although no genetic variants reached the genome-wide significance level (P < 5 × 10- 8), 28 SNPs exceeded the level of a suggestive association (P < 1 × 10- 5). One promising genetic region (2q33.1) around rs10931893 (P = 1.53 × 10- 7) was found. After imputing untyped SNPs, we found that rs60106404 (P = 2.38 × 10- 8) located at SPATS2L reached the genome-wide significance level, and 216 SNPs exceeded the level of a suggestive association. We found 1007 genes nominally associated with the FPG level (P < 0.05), including SPATS2L, KCNK5, ADCY5, PCSK1, PTPRA, and SLC26A11. Moreover, C1orf74 (P = 0.014) and SLC26A11 (P = 0.021) were differentially expressed between patients with impaired fasting glucose and healthy controls. Some important enriched biological pathways, such as β-alanine metabolism, regulation of insulin secretion, glucagon signaling in metabolic regulation, IL-1 receptor pathway, signaling by platelet derived growth factor, cysteine and methionine metabolism pathway, were identified. CONCLUSIONS: The FPG level is highly heritable in the Chinese population, and genetic variants are significantly involved in regulatory domains, functional genes and biological pathways that mediate FPG levels. This study provides important clues for further elucidating the molecular mechanism of glucose homeostasis and discovering new diagnostic biomarkers and therapeutic targets for diabetes.
BACKGROUND/OBJECTIVES: Neck circumference, an index of upper airway fat, has been suggested to be an important measure of body-fat distribution with unique associations with health outcomes such as obstructive sleep apnea and metabolic disease. This study aims to study the genetic bases of neck circumference. METHODS: We conducted a multi-ethnic genome-wide association study of neck circumference, adjusted and unadjusted for BMI, in up to 15,090 European Ancestry (EA) and African American (AA) individuals. Because sexually dimorphic associations have been observed for anthropometric traits, we conducted both sex-combined and sex-specific analysis. RESULTS: We identified rs227724 near the Noggin (NOG) gene as a possible quantitative locus for neck circumference in men (N = 8831, P = 1.74 × 10-9) but not in women (P = 0.08). The association was replicated in men (N = 1554, P = 0.045) in an independent dataset. This locus was previously reported to be associated with human height and with self-reported snoring. We also identified rs13087058 on chromosome 3 as a suggestive locus in sex-combined analysis (N = 15090, P = 2.94 × 10-7; replication P =0.049). This locus was also associated with electrocardiogram-assessed PR interval and is a cis-expression quantitative locus for the PDZ Domain-containing ring finger 2 (PDZRN3) gene. Both NOG and PDZRN3 interact with members of transforming growth factor-beta superfamily signaling proteins. CONCLUSIONS: Our study suggests that neck circumference may have unique genetic basis independent of BMI.
Molecular quantitative trait locus (QTL) analyses are increasingly popular to explore the genetic architecture of complex traits, but existing studies do not leverage shared regulatory patterns and suffer from a large multiplicity burden, which hampers the detection of weak signals such as trans associations. Here, we present a fully multivariate proteomic QTL (pQTL) analysis performed with our recently proposed Bayesian method LOCUS on data from two clinical cohorts, with plasma protein levels quantified by mass-spectrometry and aptamer-based assays. Our two-stage study identifies 136 pQTL associations in the first cohort, of which >80% replicate in the second independent cohort and have significant enrichment with functional genomic elements and disease risk loci. Moreover, 78% of the pQTLs whose protein abundance was quantified by both proteomic techniques are confirmed across assays. Our thorough comparisons with standard univariate QTL mapping on (1) these data and (2) synthetic data emulating the real data show how LOCUS borrows strength across correlated protein levels and markers on a genome-wide scale to effectively increase statistical power. Notably, 15% of the pQTLs uncovered by LOCUS would be missed by the univariate approach, including several trans and pleiotropic hits with successful independent validation. Finally, the analysis of extensive clinical data from the two cohorts indicates that the genetically-driven proteins identified by LOCUS are enriched in associations with low-grade inflammation, insulin resistance and dyslipidemia and might therefore act as endophenotypes for metabolic diseases. While considerations on the clinical role of the pQTLs are beyond the scope of our work, these findings generate useful hypotheses to be explored in future research; all results are accessible online from our searchable database. Thanks to its efficient variational Bayes implementation, LOCUS can analyze jointly thousands of traits and millions of markers. Its applicability goes beyond pQTL studies, opening new perspectives for large-scale genome-wide association and QTL analyses. Diet, Obesity and Genes (DiOGenes) trial registration number: NCT00390637.
CONTEXT: Estradiol is the primary female sex hormone and plays an important role for skeletal health in both sexes. Several enzymes are involved in estradiol metabolism, but few genome-wide association studies (GWAS) have been performed to characterize the genetic contribution to variation in estrogen levels. OBJECTIVE: Identify genetic loci affecting estradiol levels and estimate causal effect of estradiol on bone mineral density (BMD). DESIGN: We performed GWAS for estradiol in males (n = 147 690) and females (n = 163 985) from UK Biobank. Estradiol was analyzed as a binary phenotype above/below detection limit (175 pmol/L). We further estimated the causal effect of estradiol on BMD using Mendelian randomization. RESULTS: We identified 14 independent loci associated (P < 5 × 10-8) with estradiol levels in males, of which 1 (CYP3A7) was genome-wide and 7 nominally (P < 0.05) significant in females. In addition, 1 female-specific locus was identified. Most loci contain functionally relevant genes that have not been discussed in relation to estradiol levels in previous GWAS (eg, SRD5A2, which encodes a steroid 5-alpha reductase that is involved in processing androgens, and UGT3A1 and UGT2B7, which encode enzymes likely to be involved in estradiol elimination). The allele that tags the O blood group at the ABO locus was associated with higher estradiol levels. We identified a causal effect of high estradiol levels on increased BMD in both males (P = 1.58 × 10-11) and females (P = 7.48 × 10-6). CONCLUSION: Our findings further support the importance of the body's own estrogen to maintain skeletal health in males and in females.
Testosterone supplementation is commonly used for its effects on sexual function, bone health and body composition, yet its effects on disease outcomes are unknown. To better understand this, we identified genetic determinants of testosterone levels and related sex hormone traits in 425,097 UK Biobank study participants. Using 2,571 genome-wide significant associations, we demonstrate that the genetic determinants of testosterone levels are substantially different between sexes and that genetically higher testosterone is harmful for metabolic diseases in women but beneficial in men. For example, a genetically determined 1 s.d. higher testosterone increases the risks of type 2 diabetes (odds ratio (OR) = 1.37 (95% confidence interval (95% CI): 1.22-1.53)) and polycystic ovary syndrome (OR = 1.51 (95% CI: 1.33-1.72)) in women, but reduces type 2 diabetes risk in men (OR = 0.86 (95% CI: 0.76-0.98)). We also show adverse effects of higher testosterone on breast and endometrial cancers in women and prostate cancer in men. Our findings provide insights into the disease impacts of testosterone and highlight the importance of sex-specific genetic analyses.
Total testosterone levels
Sex hormone-binding globulin levels
Estradiol levels
Bioavailable testosterone levels
Sex hormone-binding globulin levels adjusted for BMI
Loci identified in genome-wide association studies (GWAS) can include multiple distinct association signals. We sought to identify the molecular basis of multiple association signals for adiponectin, a hormone involved in glucose regulation secreted almost exclusively from adipose tissue, identified in the Metabolic Syndrome in Men (METSIM) study. With GWAS data for 9,262 men, four loci were significantly associated with adiponectin: ADIPOQ, CDH13, IRS1, and PBRM1. We performed stepwise conditional analyses to identify distinct association signals, a subset of which are also nearly independent (lead variant pairwise r2<0.01). Two loci exhibited allelic heterogeneity, ADIPOQ and CDH13. Of seven association signals at the ADIPOQ locus, two signals colocalized with adipose tissue expression quantitative trait loci (eQTLs) for three transcripts: trait-increasing alleles at one signal were associated with increased ADIPOQ and LINC02043, while trait-increasing alleles at the other signal were associated with decreased ADIPOQ-AS1. In reporter assays, adiponectin-increasing alleles at two signals showed corresponding directions of effect on transcriptional activity. Putative mechanisms for the seven ADIPOQ signals include a missense variant (ADIPOQ G90S), a splice variant, a promoter variant, and four enhancer variants. Of two association signals at the CDH13 locus, the first signal consisted of promoter variants, including the lead adipose tissue eQTL variant for CDH13, while a second signal included a distal intron 1 enhancer variant that showed ~2-fold allelic differences in transcriptional reporter activity. Fine-mapping and experimental validation demonstrated that multiple, distinct association signals at these loci can influence multiple transcripts through multiple molecular mechanisms.
BACKGROUND: Circulating lipoprotein lipids cause coronary heart disease (CHD). However, the precise way in which one or more lipoprotein lipid-related entities account for this relationship remains unclear. Using genetic instruments for lipoprotein lipid traits implemented through multivariable Mendelian randomisation (MR), we sought to compare their causal roles in the aetiology of CHD. METHODS AND FINDINGS: We conducted a genome-wide association study (GWAS) of circulating non-fasted lipoprotein lipid traits in the UK Biobank (UKBB) for low-density lipoprotein (LDL) cholesterol, triglycerides, and apolipoprotein B to identify lipid-associated single nucleotide polymorphisms (SNPs). Using data from CARDIoGRAMplusC4D for CHD (consisting of 60,801 cases and 123,504 controls), we performed univariable and multivariable MR analyses. Similar GWAS and MR analyses were conducted for high-density lipoprotein (HDL) cholesterol and apolipoprotein A-I. The GWAS of lipids and apolipoproteins in the UKBB included between 393,193 and 441,016 individuals in whom the mean age was 56.9 y (range 39-73 y) and of whom 54.2% were women. The mean (standard deviation) lipid concentrations were LDL cholesterol 3.57 (0.87) mmol/L and HDL cholesterol 1.45 (0.38) mmol/L, and the median triglycerides was 1.50 (IQR = 1.11) mmol/L. The mean (standard deviation) values for apolipoproteins B and A-I were 1.03 (0.24) g/L and 1.54 (0.27) g/L, respectively. The GWAS identified multiple independent SNPs associated at P < 5 × 10-8 for LDL cholesterol (220), apolipoprotein B (n = 255), triglycerides (440), HDL cholesterol (534), and apolipoprotein A-I (440). Between 56%-93% of SNPs identified for each lipid trait had not been previously reported in large-scale GWASs. Almost half (46%) of these SNPs were associated at P < 5 × 10-8 with more than one lipid-related trait. Assessed individually using MR, LDL cholesterol (odds ratio [OR] 1.66 per 1-standard-deviation-higher trait; 95% CI: 1.49-1.86; P < 0.001), triglycerides (OR 1.34; 95% CI: 1.25-1.44; P < 0.001) and apolipoprotein B (OR 1.73; 95% CI: 1.56-1.91; P < 0.001) had effect estimates consistent with a higher risk of CHD. In multivariable MR, only apolipoprotein B (OR 1.92; 95% CI: 1.31-2.81; P < 0.001) retained a robust effect, with the estimate for LDL cholesterol (OR 0.85; 95% CI: 0.57-1.27; P = 0.44) reversing and that of triglycerides (OR 1.12; 95% CI: 1.02-1.23; P = 0.01) becoming weaker. Individual MR analyses showed a 1-standard-deviation-higher HDL cholesterol (OR 0.80; 95% CI: 0.75-0.86; P < 0.001) and apolipoprotein A-I (OR 0.83; 95% CI: 0.77-0.89; P < 0.001) to lower the risk of CHD, but these effect estimates attenuated substantially to the null on accounting for apolipoprotein B. A limitation is that, owing to the nature of lipoprotein metabolism, measures related to the composition of lipoprotein particles are highly correlated, creating a challenge in making exclusive interpretations on causation of individual components. CONCLUSIONS: These findings suggest that apolipoprotein B is the predominant trait that accounts for the aetiological relationship of lipoprotein lipids with risk of CHD.
Although skeletal muscle plays a crucial role in metabolism and influences aging and chronic diseases, little is known about the genetic variations with skeletal muscle, especially in the Asian population. We performed a genome-wide association study in 2,046 participants drawn from a population-based study. Appendicular skeletal muscle mass was estimated based on appendicular lean soft tissue measured with a multi-frequency bioelectrical impedance analyzer and divided by height squared to derive the skeletal muscle index (SMI). After conducting quality control and imputing the genotypes, we analyzed 6,391,983 autosomal SNPs. A genome-wide significant association was found for the intronic variant rs138684936 in the NEB and RIF1 genes (β = 0.217, p = 6.83 × 10-9). These two genes are next to each other and are partially overlapped on chr2q23. We conducted extensive functional annotations to gain insight into the directional biological implication of significant genetic variants. A gene-based analysis identified the significant TNFSF9 gene and confirmed the suggestive association of the NEB gene. Pathway analyses showed the significant association of regulation of multicellular organism growth gene-set and the suggestive associations of pathways related to skeletal system development or skeleton morphogenesis with SMI. In conclusion, we identified a new genetic locus on chromosome 2 for SMI with genome-wide significance. These results enhance the biological understanding of skeletal muscle mass and provide specific leads for functional experiments.
Many early studies presented beneficial effects of polyunsaturated fatty acids (PUFA) on cardiovascular risk factors and disease. However, results from recent meta-analyses indicate that this effect would be very low or nil. One of the factors that may contribute to the inconsistency of the results is that, in most studies, genetic factors have not been taken into consideration. It is known that fatty acid desaturase (FADS) gene cluster in chromosome 11 is a very important determinant of plasma PUFA, and that the prevalence of the single nucleotide polymorphisms (SNPs) varies greatly between populations and may constitute a bias in meta-analyses. Previous genome-wide association studies (GWAS) have been carried out in other populations and none of them have investigated sex and Mediterranean dietary pattern interactions at the genome-wide level. Our aims were to undertake a GWAS to discover the genes most associated with serum PUFA concentrations (omega-3, omega-6, and some fatty acids) in a scarcely studied Mediterranean population with metabolic syndrome, and to explore sex and adherence to Mediterranean diet (MedDiet) interactions at the genome-wide level. Serum PUFA were determined by NMR spectroscopy. We found strong robust associations between various SNPs in the FADS cluster and omega-3 concentrations (top-ranked in the adjusted model: FADS1-rs174547, p = 3.34 × 10-14; FADS1-rs174550, p = 5.35 × 10-14; FADS2-rs1535, p = 5.85 × 10-14; FADS1-rs174546, p = 6.72 × 10-14; FADS2-rs174546, p = 9.75 × 10-14; FADS2- rs174576, p = 1.17 × 10-13; FADS2-rs174577, p = 1.12 × 10-12, among others). We also detected a genome-wide significant association with other genes in chromosome 11: MYRF (myelin regulatory factor)-rs174535, p = 1.49 × 10-12; TMEM258 (transmembrane protein 258)-rs102275, p = 2.43 × 10-12; FEN1 (flap structure-specific endonuclease 1)-rs174538, p = 1.96 × 10-11). Similar genome-wide statistically significant results were found for docosahexaenoic fatty acid (DHA). However, no such associations were detected for omega-6 PUFAs or linoleic acid (LA). For total PUFA, we observed a consistent gene*sex interaction with the DNTTIP2 (deoxynucleotidyl transferase terminal interacting protein 2)-rs3747965 p = 1.36 × 10-8. For adherence to MedDiet, we obtained a relevant interaction with the ME1 (malic enzyme 1) gene (a gene strongly regulated by fat) in determining serum omega-3. The top-ranked SNP for this interaction was ME1-rs3798890 (p = 2.15 × 10-7). In the regional-wide association study, specifically focused on the FADS1/FASD2/FADS3 and ELOVL (fatty acid elongase) 2/ELOVL 5 regions, we detected several statistically significant associations at p < 0.05. In conclusion, our results confirm a robust role of the FADS cluster on serum PUFA in this population, but the associations vary depending on the PUFA. Moreover, the detection of some sex and diet interactions underlines the need for these associations/interactions to be studied in all specific populations so as to better understand the complex metabolism of PUFA.
Serum docosahexaenoic fatty acid concentration in metabolic syndrome
Serum omega-3 polyunsaturated fatty acid concentration in metabolic syndrome
Serum total polyunsaturated fatty acid concentration in metabolic syndrome
omega-6:omega-3 ratio
linoleic acid
omega-6 PUFA
Serum omega-6 to omega-3 polyunsaturated fatty acid ratio in metabolic syndrome
omega-3 PUFA
Serum linoleic acid concentration in metabolic syndrome
Serum omega-6 polyunsaturated fatty acid concentration in metabolic syndrome
While the Arabian population has a high prevalence of metabolic disorders, it has not been included in global studies that identify genetic risk loci for metabolic traits. Determining the transferability of such largely Euro-centric established risk loci is essential to transfer the research tools/resources, and drug targets generated by global studies to a broad range of ethnic populations. Further, consideration of populations such as Arabs, that are characterized by consanguinity and a high level of inbreeding, can lead to identification of novel risk loci. We imputed published GWAS data from two Kuwaiti Arab cohorts (n = 1434 and 1298) to the 1000 Genomes Project haplotypes and performed meta-analysis for associations with 13 metabolic traits. We compared the observed association signals with those established for metabolic traits. Our study highlighted 70 variants from 9 different genes, some of which have established links to metabolic disorders. By relaxing the genome-wide significance threshold, we identified 'novel' risk variants from 11 genes for metabolic traits. Many novel risk variant association signals were observed at or borderline to genome-wide significance. Furthermore, 349 previously established variants from 187 genes were validated in our study. Pleiotropic effect of risk variants on multiple metabolic traits were observed. Fine-mapping illuminated rs7838666/CSMD1 rs1864163/CETP and rs112861901/[INTS10,LPL] as candidate causal variants influencing fasting plasma glucose and high-density lipoprotein levels. Computational functional analysis identified a variety of gene regulatory signals around several variants. This study enlarges the population ancestry diversity of available GWAS and elucidates new variants in an ethnic group burdened with metabolic disorders.
Fibroblast growth factors (FGFs) 21 and 23 are recently identified hormones regulating metabolism of glucose, lipid, phosphate and vitamin D. Here we conducted a genome-wide association study (GWAS) for circulating FGF21 and FGF23 concentrations to identify their genetic determinants. We enrolled 5,000 participants from Taiwan Biobank for this GWAS. After excluding participants with diabetes mellitus and quality control, association of single nucleotide polymorphisms (SNPs) with log-transformed FGF21 and FGF23 serum concentrations adjusted for age, sex and principal components of ancestry were analyzed. A second model additionally adjusted for body mass index (BMI) and a third model additionally adjusted for BMI and estimated glomerular filtration rate (eGFR) were used. A total of 4,201 participants underwent GWAS analysis. rs67327215, located within RGS6 (a gene involved in fatty acid synthesis), and two other SNPs (rs12565114 and rs9520257, located between PHC2-ZSCAN20 and ARGLU1-FAM155A respectively) showed suggestive associations with serum FGF21 level (P = 6.66 × 10-7, 6.00 × 10-7 and 6.11 × 10-7 respectively). The SNPs rs17111495 and rs17843626 were significantly associated with FGF23 level, with the former near PCSK9 gene and the latter near HLA-DQA1 gene (P = 1.04 × 10-10 and 1.80 × 10-8 respectively). SNP rs2798631, located within the TGFB2 gene, was suggestively associated with serum FGF23 level (P = 4.97 × 10-7). Additional adjustment for BMI yielded similar results. For FGF23, further adjustment for eGFR had similar results. We conducted the first GWAS of circulating FGF21 levels to date. Novel candidate genetic loci associated with circulating FGF21 or FGF23 levels were found. Further replication and functional studies are needed to support our findings.
We investigated changes in blood pressure (BP) and metabolic adverse effects, especially elevation of uric acid (UA), after treatment with a thiazide-like diuretic (TD) in patients with essential hypertension. Furthermore, the role of genetic factors in the elevation of UA by TD was assessed by a 500 K SNP DNA microarray. The subjects included 126 hypertensive patients (57 women and 69 men, mean age 59 ± 12 years) who registered for the GEANE (Gene Evaluation for ANtihypertensive Effects) study. After one month of the nontreatment period, TD, indapamide, angiotensin II receptor antagonist valsartan, and Ca channel blocker amlodipine were administered to all patients for 3 months each in a randomized crossover manner. BP, renal function, serum UA level, and electrolytes were measured at baseline and at the end of each treatment period. Single nucleotide polymorphisms (SNPs) associated with UA elevation after treatment with indapamide were investigated by a genome-wide association study (GWAS). Indapamide significantly decreased both office and home BP levels. Treatment with indapamide also significantly reduced the estimated glomerular filtration rate and serum potassium and increased serum UA. Patients whose UA level increased more than 1 mg/dl showed significantly higher baseline office SBP and plasma glucose and showed greater decline in renal function compared with those who showed less UA increase (<1 mg/dl). Some SNPs strongly associated with an increase in UA after treatment with indapamide were identified. This study is the first report on SNPs associated with UA elevation after TD treatment. This information may be useful for the prevention of adverse effects after treatment with TD.
Uric acid elevation in response to thiazide-like diuretic in hypertension
Experimental, observational, and clinical trials support a critical role of folate one-carbon metabolism (FOCM) in colorectal cancer (CRC) development. In this report, we focus on understanding the relationship between common genetic variants and metabolites of FOCM. We conducted a genome-wide association study of FOCM biomarkers among 1,788 unaffected (without CRC) individuals of European ancestry from the Colon Cancer Family Registry. Twelve metabolites, including 5-methyltetrahydrofolate, vitamin B2 (flavin mononucleotide and riboflavin), vitamin B6 (4-pyridoxic acid, pyridoxal, and pyridoxamine), total homocysteine, methionine, S-adenosylmethionine, S-adenosylhomocysteine, cystathionine, and creatinine were measured from plasma using liquid chromatography-mass spectrometry (LC-MS) or LC-MS/MS. For each individual biomarker, we estimated genotype array-specific associations followed by a fixed-effect meta-analysis. We identified the variant rs35976024 (at 2p11.2 and intronic of ATOH8) associated with total homocysteine (p = 4.9 × 10-8 ). We found a group of six highly correlated variants on chromosome 15q14 associated with cystathionine (all p < 5 × 10-8 ), with the most significant variant rs28391580 (p = 2.8 × 10-8 ). Two variants (rs139435405 and rs149119426) on chromosome 14q13 showed significant (p < 5 × 10-8 ) associations with S-adenosylhomocysteine. These three biomarkers with significant associations are closely involved in homocysteine metabolism. Furthermore, when assessing the principal components (PCs) derived from seven individual biomarkers, we identified the variant rs12665366 (at 6p25.3 and intronic of EXOC2) associated with the first PC (p = 2.3 × 10-8 ). Our data suggest that common genetic variants may play an important role in FOCM, particularly in homocysteine metabolism.
Hypertension (HTN) is a significant risk factor for cardiovascular morbidity and mortality. Metabolic abnormalities, including adverse cholesterol and triglycerides (TG) profiles, are frequent comorbid findings with HTN and contribute to cardiovascular disease. Diuretics, which are used to treat HTN and heart failure, have been associated with worsening of fasting lipid concentrations. Genome-wide meta-analyses with 39,710 European-ancestry (EA) individuals and 9925 African-ancestry (AA) individuals were performed to identify genetic variants that modify the effect of loop or thiazide diuretic use on blood lipid concentrations. Both longitudinal and cross sectional data were used to compute cohort-specific interaction results, which were then combined through meta-analysis in each ancestry. These ancestry-specific results were further combined through trans-ancestry meta-analysis. Analysis of EA data identified two genome-wide significant (p < 5 × 10-8) loci with single nucleotide variant (SNV)-loop diuretic interaction on TG concentrations (including COL11A1). Analysis of AA data identified one genome-wide significant locus adjacent to BMP2 with SNV-loop diuretic interaction on TG concentrations. Trans-ancestry analysis strengthened evidence of association for SNV-loop diuretic interaction at two loci (KIAA1217 and BAALC). There were few significant SNV-thiazide diuretic interaction associations on TG concentrations and for either diuretic on cholesterol concentrations. Several promising loci were identified that may implicate biologic pathways that contribute to adverse metabolic side effects from diuretic therapy.
Triglyceride levels x thiazide or thiazide-like diuretics use interaction
Triglyceride levels x loop diuretics use interaction
HDL cholesterol levels x loop diuretics use interaction
HDL cholesterol levels x thiazide or thiazide-like diuretics use interaction
LDL cholesterol levels x thiazide or thiazide-like diuretics use interaction
LDL cholesterol levels x loop diuretics use interaction
OBJECTIVE: Body mass index (BMI) is commonly used to assess obesity, which is associated with numerous diseases and negative health outcomes. BMI has been shown to be a heritable, polygenic trait, with close to 100 loci previously identified and replicated in multiple populations. We aim to replicate known BMI loci and identify novel associations in a trans-ethnic study population. SUBJECTS: Using eligible participants from the Population Architecture using Genomics and Epidemiology consortium, we conducted a trans-ethnic meta-analysis of 102 514 African Americans, Hispanics, Asian/Native Hawaiian, Native Americans and European Americans. Participants were genotyped on over 200 000 SNPs on the Illumina Metabochip custom array, or imputed into the 1000 Genomes Project (Phase I). Linear regression of the natural log of BMI, adjusting for age, sex, study site (if applicable), and ancestry principal components, was conducted for each race/ethnicity within each study cohort. Race/ethnicity-specific, and combined meta-analyses used fixed-effects models. RESULTS: We replicated 15 of 21 BMI loci included on the Metabochip, and identified two novel BMI loci at 1q41 (rs2820436) and 2q31.1 (rs10930502) at the Metabochip-wide significance threshold (P<2.5 × 10-7). Bioinformatic functional investigation of SNPs at these loci suggests a possible impact on pathways that regulate metabolism and adipose tissue. CONCLUSION: Conducting studies in genetically diverse populations continues to be a valuable strategy for replicating known loci and uncovering novel BMI associations.
Genotype-by-environment interaction (GEI) is a fundamental component in understanding complex trait variation. However, it remains challenging to identify genetic variants with GEI effects in humans largely because of the small effect sizes and the difficulty of monitoring environmental fluctuations. Here, we demonstrate that GEI can be inferred from genetic variants associated with phenotypic variability in a large sample without the need of measuring environmental factors. We performed a genome-wide variance quantitative trait locus (vQTL) analysis of ~5.6 million variants on 348,501 unrelated individuals of European ancestry for 13 quantitative traits in the UK Biobank and identified 75 significant vQTLs with P < 2.0 × 10-9 for 9 traits, especially for those related to obesity. Direct GEI analysis with five environmental factors showed that the vQTLs were strongly enriched with GEI effects. Our results indicate pervasive GEI effects for obesity-related traits and demonstrate the detection of GEI without environmental data.
Metabolites are small intermediate products of cellular metabolism perturbed in a variety of complex disorders. Identifying genetic markers associated with metabolite concentrations could delineate disease-related metabolic pathways in humans. We tested genetic variants for associations with 136 metabolites in 1954 Chinese from Singapore. At a conservative genome-wide threshold (3.7 × 10-10), we detected 1899 variant-metabolite associations at 16 genetic loci. Three loci (ABCA7, A4GALT, GSTM2) represented novel associations with metabolites, with the strongest association observed between ABCA7 and d18:1/24:1 dihexosylceramide. Among 13 replicated loci, we identified six new variants independent of previously reported metabolite or lipid signals. We observed variant-metabolite associations at two loci (ABCA7, CHCHD2) that have been linked to neurodegenerative diseases. At SGPP1 and SPTLC3 loci, genetic variants showed preferential selectivity for sphingolipids with d16 (rather than d18) sphingosine backbone, including sphingosine-1-phosphate (S1P). Our results provide new genetic associations for metabolites and highlight the role of metabolites as intermediate modulators in disease metabolic pathways.