CHARGE Consortium Research Articles

Validation and utility of plasma neurofilament light as a biomarker for vascular cognitive impairment

AbstractBackgroundNeurofilament light chain (NfL) is a broad marker of neuroaxonal injury that is elevated in the CSF in those with vascular cognitive impairment and dementia (VCID). Blood and CSF levels highly correlate, making it an attractive peripheral marker for VCID pathology. As part of the MarkVCID consortium, we sought to evaluate the instrumental validity of plasma NfL using the Quanterix Simoa platform and assess its validity for risk stratification in clinical trials of VCID.MethodPlasma NfL was measured using HD‐X and HD‐1 Simoa instruments. For instrumental validation, we used samples from the MarkVCID consortium to evaluate intra‐ and inter‐plate reliability, test‐retest repeatability, and inter‐site reproducibility. We used linear regression models to assess the association of NfL with general cognitive function (GCF) as the primary outcome. In secondary analyses we assessed associations with white matter hyperintensities (WMH), an established small vessel disease marker. Models were adjusted for potential confounders. The clinical validation included established cohorts from the CHARGE consortium (i.e., CARDIA, ARIC, FHS, AGES; n=4,772), the UKY ADRC (n=350), and the UCD ADRC (n=196). Additional analyses are underway in MarkVCID sites.ResultWe found low coefficients of variation (average CV<12%), high inter‐site reproducibility (overall ICC = 0.93) and high repeatability in blood samples drawn within 30 days (ICC=0.968). There was high consistency across Quanterix instruments (HD‐X and HD‐1; R2≥0.98) and kits (N4PA and single molecule NfL; ICC≥0.81). We observed consistent significant associations between higher NfL concentrations and worse GCF in CHARGE cohorts (meta‐analysis β=‐0.11; [95% CI ‐0.06; ‐0.17]), the UKY ADRC (β=‐0.16; [95% CI ‐0.27; ‐0.05]) and the UCD ADRC (UCD: β=‐0.28; [95% CI ‐0.48; ‐0.08). Secondary analyses revealed significant associations between elevated NfL concentrations and higher WMH burden in CHARGE cohorts and the UCD ADRC (P<0.01).ConclusionOur results suggest plasma NfL can be reliably measured using the Quanterix platform, making this marker ideal for multi‐site clinical trials. We observed consistent associations for plasma NfL concentrations with cognition and WMH across independent samples, providing evidence that plasma NfL can be a useful biomarker for stratification in VCID trials.

Serial 7-Day Electrocardiogram PatchScreening for AF inHigh-Risk Older Women by the CHARGE-AF Score.

Asymptomatic atrial fibrillation (AF) is associated with an increased risk of stroke. The yield of serial electrocardiographic (ECG) screening for AF is unknown. The aim of this study was to determine the frequency of AF detected by serial, 7-day ECG patch screenings in older women identified as having an elevated risk of AF according to the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology)-AF clinical prediction score. Postmenopausal women with a 5-year predicted risk of new-onset AF≥5% according to CHARGE-AF were recruited from the ongoing WHISH (Women's Health Initiative Strong and Healthy) randomized trial of a physical activity intervention. Participants with AF at baseline by self-report or medical records review were excluded. Screening with 7-day ECG patch monitors was performed at baseline, 6months, and 12months from study enrollment. On baseline monitoring, 2.5% of the cohort had AF detected, increasing to 3.7% by 6months and 4.9% cumulatively by 12months. Yield of patch screening was higher among participants with a higher (≥10%) CHARGE-AF score: 4.2% had AF detected at baseline, 5.9% at 6months, and 7.2% at 12months. Most participants with patch-identified AF never had a clinical diagnosis of AF (36 of 46 [78%]). Older women with an elevated CHARGE-AF score had a high prevalence of AF on 7-day ECG patch screening. Serial screening over 12months substantially increased the detection of AF. These data can be useful in helping identify high-risk participants for enrollment in future studies of the management of asymptomatic AF.(Women'sHealth Initiative Silent Atrial Fibrillation Recording Study [WHISH STAR]; NCT05366803.).

Exploring potential shared genetic influences between rheumatoid arthritis and blood lipid levels

Background and aimsThe association between rheumatoid arthritis (RA) and blood lipid levels has often been described as paradoxical, despite the strong association between RA and cardiovascular disease (CVD) risk. We aimed to clarify the genetic architecture that would explain the relationship between RA and blood-lipid levels, while considering inflammation as measured by C-reactive protein (CRP). MethodsGenome-wide association study (GWAS) summary statistics were collected from the CHARGE Consortium and Global Lipids Genetics Consortium. Blood-lipid levels includes HDL-C, LDL-C, triglycerides (TG), and total cholesterol (TC). Causality was examined by assessing Mendelian Randomization (MR) analysis. Pleiotropy, the identification of shared causal variants between traits, was assessed by conducting colocalization analyses. ResultsUsing the MR Egger method, RA did not appear to causally predict alterations in lipid factors, rather the MR Egger intercept revealed that the genetic relationship between RA and HDL-C, LDL-C and TC may be explained by horizontal pleiotropy (p=0.003, 0.006, and 0.018, respectively). MR was suggestive of a horizontally pleiotropic relationship between CRP and lipid factors, while a causal relationship could not be ruled out. Recurring genes arising from shared causal genetic variants between RA and varying lipid factors included NAT2/PSD3, FADS2/FADS1, SH2B3, and YDJC. ConclusionsHorizontal pleiotropy appears to explain the genetic relationship between RA and blood-lipid levels. In addition, blood-lipid levels appear to suggest a horizontally pleiotropic relationship to CRP, if not mediated through RA as well. Consideration of the pleiotropic genes between RA and blood lipid levels may aid in enhancing diagnostic means to predict CVD.

Plasma polyunsaturated fatty acid concentrations and sleep apnea risk: A two-sample Mendelian randomization study.

BackgroundPrevious observational studies have found that lower levels of circulating polyunsaturated fatty acids (PUFAs) were associated with a higher risk of sleep apnea (SA). However, the causality of the association remains unclear.Materials and methodsWe used the two-sample Mendelian randomization (MR) study to assess the causal association of omega-3 and omega-6 fatty acids with SA. Single-nucleotide polymorphisms (SNPs) predicting the plasma level of PUFAs at the suggestive genome-wide significance level (p < 5 × 10–6) were selected as instrumental variables (IVs) from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) (n = ∼8,000) Consortium. For outcomes, the summary-level statistics of SA were obtained from the latest genome-wide association study (GWAS), which combined five cohorts with a total number of 25,008 SA cases and 172,050 snoring cases (total = 523,366).ResultsWe found no association of α-linolenic acid (ALA) [odds ratio (OR) = 1.09 per% changed, 95% confidence interval (CI) 0.67–1.78], eicosapentaenoic acid (EPA) (OR = 0.94, 95% CI 0.88–1.01), docosapentaenoic acid (DPA) (OR = 0.95, 95% CI 0.88–1.02), and docosahexaenoic acid (DHA) (OR = 0.99, 95% CI 0.96–1.02) with the risk of SA using inverse-variance weighted (IVW) method. Moreover, for omega-6 PUFAs, no association between linoleic acid (LA) (OR = 0.98, 95% CI 0.96–1.01), arachidonic acid (AA) (1.00, 95% CI 0.99–1.01), and adrenic acid (AdrA) (0.93, 95% CI 0.71–1.21) with the risk of SA was found. Similarly, no associations of PUFAs with SA were found in single-locus MR analysis.ConclusionIn the current study, we first found that there is no genetic evidence to support the causal role of omega-3 and omega-6 PUFAs in the risk of SA. From a public health perspective, our findings refute the notion that consumption of foods rich in PUFAs or the use of PUFAs supplementation can reduce the risk of SA.

Serum Fetuin-A and Risk of Gestational Diabetes Mellitus: An Observational Study and Mendelian Randomization Analysis.

Fetuin-A was reported to be associated with risk of type 2 diabetes, but its association with incident gestational diabetes mellitus (GDM) was less studied. We aimed to examine the association between fetuin-A levels in early pregnancy and risk of incident GDM and to evaluate whether this association was causal. A total of 332 pregnant women with GDM and 664 matched controls were included in this nested case-control study. Multivariable conditional logistic regression was applied to investigate the prospective association between serum fetuin-A in early pregnancy and subsequent risk of GDM. Two-sample Mendelian randomization (MR) analysis was used to examine the causal association, using summary statistics from the CHARGE Consortium and the FinnGen consortium. The mean age of the participants was 28.0 years, and the mean gestational age was 11.0 weeks (range 6-15) at enrollment. In the final model, the odds ratio (OR) for GDM comparing the extreme quartiles of fetuin-A levels was 1.78 (95% CI 1.06, 2.98; P for trend = 0.009), and the restricted cubic spline analysis indicated a linear association (P for nonlinearity = 0.83). This positive association was found in women with waist circumference <80 cm but not in those with waist circumference ≥80 cm (P for interaction = 0.04). However, MR analyses showed no evidence of a causal association with an OR of 0.91 (95% CI 0.67, 1.23) per unit increment of fetuin-A. Serum fetuin-A levels in early pregnancy were positively associated with risk of GDM, particularly in those with normal waist circumference. However, we found no genetic evidence for a causal association.

Genetic analysis of over half a million people characterises C-reactive protein loci

Chronic low-grade inflammation is linked to a multitude of chronic diseases. We report the largest genome-wide association study (GWAS) on C-reactive protein (CRP), a marker of systemic inflammation, in UK Biobank participants (N = 427,367, European descent) and the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium (total N = 575,531 European descent). We identify 266 independent loci, of which 211 are not previously reported. Gene-set analysis highlighted 42 gene sets associated with CRP levels (p ≤ 3.2 ×10−6) and tissue expression analysis indicated a strong association of CRP related genes with liver and whole blood gene expression. Phenome-wide association study identified 27 clinical outcomes associated with genetically determined CRP and subsequent Mendelian randomisation analyses supported a causal association with schizophrenia, chronic airway obstruction and prostate cancer. Our findings identified genetic loci and functional properties of chronic low-grade inflammation and provided evidence for causal associations with a range of diseases.

Type 2 Diabetes Partitioned Polygenic Scores Associate With Disease Outcomes in 454,193 Individuals Across 13 Cohorts.

OBJECTIVEType 2 diabetes (T2D) has heterogeneous patient clinical characteristics and outcomes. In previous work, we investigated the genetic basis of this heterogeneity by clustering 94 T2D genetic loci using their associations with 47 diabetes-related traits and identified five clusters, termed β-cell, proinsulin, obesity, lipodystrophy, and liver/lipid. The relationship between these clusters and individual-level metabolic disease outcomes has not been assessed.RESEARCH DESIGN AND METHODSHere we constructed individual-level partitioned polygenic scores (pPS) for these five clusters in 12 studies from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank (n = 454,193) and tested for cross-sectional association with T2D-related outcomes, including blood pressure, renal function, insulin use, age at T2D diagnosis, and coronary artery disease (CAD).RESULTSDespite all clusters containing T2D risk-increasing alleles, they had differential associations with metabolic outcomes. Increased obesity and lipodystrophy cluster pPS, which had opposite directions of association with measures of adiposity, were both significantly associated with increased blood pressure and hypertension. The lipodystrophy and liver/lipid cluster pPS were each associated with CAD, with increasing and decreasing effects, respectively. An increased liver/lipid cluster pPS was also significantly associated with reduced renal function. The liver/lipid cluster includes known loci linked to liver lipid metabolism (e.g., GCKR, PNPLA3, and TM6SF2), and these findings suggest that cardiovascular disease risk and renal function may be impacted by these loci through their shared disease pathway.CONCLUSIONSOur findings support that genetically driven pathways leading to T2D also predispose differentially to clinical outcomes.

Genome-wide analysis of mitochondrial DNA copy number reveals loci implicated in nucleotide metabolism, platelet activation, and megakaryocyte proliferation

Mitochondrial DNA copy number (mtDNA-CN) measured from blood specimens is a minimally invasive marker of mitochondrial function that exhibits both inter-individual and intercellular variation. To identify genes involved in regulating mitochondrial function, we performed a genome-wide association study (GWAS) in 465,809 White individuals from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank (UKB). We identified 133 SNPs with statistically significant, independent effects associated with mtDNA-CN across 100 loci. A combination of fine-mapping, variant annotation, and co-localization analyses was used to prioritize genes within each of the 133 independent sites. Putative causal genes were enriched for known mitochondrial DNA depletion syndromes (p = 3.09 × 10–15) and the gene ontology (GO) terms for mtDNA metabolism (p = 1.43 × 10–8) and mtDNA replication (p = 1.2 × 10–7). A clustering approach leveraged pleiotropy between mtDNA-CN associated SNPs and 41 mtDNA-CN associated phenotypes to identify functional domains, revealing three distinct groups, including platelet activation, megakaryocyte proliferation, and mtDNA metabolism. Finally, using mitochondrial SNPs, we establish causal relationships between mitochondrial function and a variety of blood cell-related traits, kidney function, liver function and overall (p = 0.044) and non-cancer mortality (p = 6.56 × 10–4).

Association of low-frequency and rare coding variants with information processing speed

Measures of information processing speed vary between individuals and decline with age. Studies of aging twins suggest heritability may be as high as 67%. The Illumina HumanExome Bead Chip genotyping array was used to examine the association of rare coding variants with performance on the Digit-Symbol Substitution Test (DSST) in community-dwelling adults participating in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. DSST scores were available for 30,576 individuals of European ancestry from nine cohorts and for 5758 individuals of African ancestry from four cohorts who were older than 45 years and free of dementia and clinical stroke. Linear regression models adjusted for age and gender were used for analysis of single genetic variants, and the T5, T1, and T01 burden tests that aggregate the number of rare alleles by gene were also applied. Secondary analyses included further adjustment for education. Meta-analyses to combine cohort-specific results were carried out separately for each ancestry group. Variants in RNF19A reached the threshold for statistical significance (p = 2.01 × 10−6) using the T01 test in individuals of European descent. RNF19A belongs to the class of E3 ubiquitin ligases that confer substrate specificity when proteins are ubiquitinated and targeted for degradation through the 26S proteasome. Variants in SLC22A7 and OR51A7 were suggestively associated with DSST scores after adjustment for education for African-American participants and in the European cohorts, respectively. Further functional characterization of its substrates will be required to confirm the role of RNF19A in cognitive function.

NIA genetics of Alzheimer's disease data storage site (NIAGADS): 2021 update.

NIAGADS is a national genomics data repository that facilitates access of genotypic and sequencing data to qualified investigators for the study of the genetics of Alzheimer's disease (AD) and related neurological diseases. Collaborations with large consortia and centers such as the Alzheimer's Disease Genetics Consortium (ADGC), Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium, the Alzheimer's Disease Sequencing Project (ADSP), and the Genome Center for Alzheimer's Disease (GCAD) allow NIAGADS to lead the effort in managing large AD datasets that can be easily accessed and fully utilized by the research community. NIAGADS is supported by National Institute on Aging (NIA) under a cooperative agreement. All data derived from NIA funded AD genetics studies are expected to be deposited in NIAGADS or another NIA approved site. NIAGADS manages a Data Sharing Service (DSS) that facilitates the deposition and sharing of genomic data and association results with approved users in the neurodegenerative research community. In addition, researchers are able to freely use the NIAGADS Alzheimer's Genomics Database (www.niagads.org/genomics/) to search annotation resources that link published AD studies to AD-relevant sequence features and genome-wide annotations. As of January 2021, NIAGADS houses 74 datasets comprised of >90,000 samples including GWAS, sequencing, gene expression, annotations, deep phenotypes, and summary statistics. Qualified investigators can retrieve ADSP sequencing data with ease and flexibility through the NIAGADS DSS. As of February 2021, the ADSP and other contributing studies have completed whole exome sequencing (WES) of 20,504 samples and whole-genome sequencing (WGS) of 16,908 samples. Raw WES and WGS files, quality controlled VCF files, and phenotype data files are available via qualified access. The next round of sequencing currently underway will generate around 18,000 additional genomes to be released at the end of 2021. NIAGADS is a rich resource for AD researchers, with the goal of facilitating advances in Alzheimer's genetics research. By housing datasets from many projects and institutions, NIAGADS enables AD researchers to meet their research goals more efficiently. Datasets, guidelines, and new features are available on our website at https://www.niagads.org.

A meta-analysis of genome-wide association studies identifies new genetic loci associated with all-cause and vascular dementia.

Dementia is multifactorial with Alzheimer (AD) and vascular (VaD) pathologies making the largest contributions. There have been over 40 genetic loci associated with AD but genome-wide associations (GWA) underlying VaD remain incompletely identified. The proportion of VaD differs across studies based on study-specific definitions. We hypothesize that common forms of dementia (AD, VaD) will share genetic risk factors. We conducted the largest GWAS to date of VaD and examined the genetic overlap with "all-cause dementia" (ACD). A total of 293,544 participants from 9 population-based CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) cohorts, 2 national case-control consortia (ADGC, MEMENTO) and the UKBB contributed 23,986 and 2,935 cases of ACD and VaD, respectively. We ran study-specific analyses adjusting for age, sex, and population structure and meta-analyzed summary statistics using the sample size weighted method implemented in METAL, followed by conditional analyses, fine-mapping and bioinformatic exploration of loci. Genome-wide associations with VaD were identified at the APOE locus and at 5 additional loci. One locus has been previously associated with hippocampal volume, verbal memory and CSF amyloid levels (ASTN2); others were near genes associated with hypertension, diabetes and hyperlipidemia (Figures 1 and 2). In addition to previously identified AD loci, we identified novel variants associated with ACD. VaD-related loci also showed sub-threshold associations with ACD that were congruent in direction of effect, thus suggesting additional biological targets underlying ACD. We will additionally present results of an ongoing multiethnic GWAS and insights from pathway analyses and bioinformatic parsing of the identified loci. Although VaD is the second most common cause of dementia, the identification of associated genetic loci has been hindered by the heterogeneity of its definition, which necessitates a large sample size to reach genome-wide significance. The newly identified loci could provide novel insights into the pathophysiological mechanisms of dementia and point to new prevention and treatment strategies.

Effect of General Adiposity and Central Body Fat Distribution on the Circulating Metabolome: A Multicohort Nontargeted Metabolomics Observational and Mendelian Randomization Study.

Obesity is associated with adverse health outcomes, but the metabolic effects have not yet been fully elucidated. We aimed to investigate the association between adiposity and circulating metabolites and to address causality with Mendelian randomization (MR). Metabolomics data were generated with nontargeted ultraperformance liquid chromatography coupled to time-of-flight mass spectrometry in plasma and serum from three population-based Swedish cohorts: ULSAM (N = 1,135), PIVUS (N = 970), and TwinGene (N = 2,059). We assessed associations of general adiposity measured as BMI and central body fat distribution measured as waist-to-hip ratio adjusted for BMI (WHRadjBMI) with 210 annotated metabolites. We used MR analysis to assess causal effects. Lastly, we attempted to replicate the MR findings in the KORA and TwinsUK cohorts (N = 7,373), the CHARGE Consortium (N = 8,631), the Framingham Heart Study (N = 2,076), and the DIRECT Consortium (N = 3,029). BMI was associated with 77 metabolites, while WHRadjBMI was associated with 11 and 3 metabolites in women and men, respectively. The MR analyses in the Swedish cohorts suggested a causal association (P value <0.05) of increased general adiposity and reduced levels of arachidonic acid, dodecanedioic acid, and lysophosphatidylcholine (P-16:0) as well as with increased creatine levels. The results of the replication effort provided support for a causal association of adiposity with reduced levels of arachidonic acid (P value = 0.03). Adiposity is associated with variation of large parts of the circulating metabolome; however, further investigation of causality is required in well-powered cohorts.

Effect of n-3 polyunsaturated fatty acids on ischemic heart disease and cardiometabolic risk factors: a two-sample Mendelian randomization study

BackgroundThe cardioprotective ability of n-3 polyunsaturated fatty acids (PUFAs) is controversial. Most studies suggest a specific role for PUFAs in cardioprotection from ischemic heart disease (IHD). However, few studies have used genetic biomarkers of n-3 PUFAs to examine their potential relationships with IHD. This study aimed to use Mendelian randomization to evaluate whether genetically-predicted n-3 PUFAs affect IHD and cardiometabolic risk factors (CRFs).MethodsGenetic variants strongly (p < 5 × 10–8) and independently (r2 > 0.1) associated with n-3 PUFAs were derived from the CHARGE Consortium (including 8,866 subjects of European ancestry) and were used as instrumental variables (IVs) for evaluating the effect of n-3 PUFAs, including α-linolenic acid (ALA), docosapentaenoic acid (DPA), docosahexaenoic acid (DHA), and eicosapentaenoic acid (EPA). Data on the associations between the IVs and IHD, myocardial infarction, and CRFs (including diabetes, lipids, blood pressure, body mass index, and waist-to-hip ratio (WHR)) were obtained from the UK Biobank SOFT CAD GWAS with the CARDIoGRAMplusC4D 1000 Genomes-based GWAS (113,937 IHD cases and 339,115 controls), the Myocardial Infarction Genetics and CARDIoGRAM Exome consortia (42,335 MI cases and 78,240 controls), the DIAbetes Genetics Replication And Meta-analysis consortium (26,676 diabetes mellitus cases and 132,532 controls), the Global Lipids Genetics Consortium (n = 196,475), the International Consortium for Blood Pressure (n = 69,395), and the meta-analysis of GWAS for body fat distribution in the UK Biobank and Genetic Investigation of Anthropometric Traits (n = 694,649).ResultsGenetically-predicted higher ALA was associated with lower risk of IHD, type 2 diabetes (T2D), and lower serum lipids. The effect size per 0.05-unit increase (about 1 standard deviation) in plasma ALA level) was − 1.173 (95% confidence interval − 2.214 to − 0.133) for IHD. DPA and EPA had no association with IHD but were associated with a higher risk of T2D, higher levels of lipids or WHR. DHA had no association with IHD or CRFs.ConclusionsOur study suggests a benefit of ALA for IHD and its main risk factors. DHA, DPA, and EPA had no association with IHD but were partly associated with increasing cardiometabolic risk factors.

Causal effect of Lipoprotein-associated phospholipase A2 activity on coronary artery disease and myocardial Infarction: A Two-Sample Mendelian Randomization study

BackgroundLipoprotein-associated phospholipase A2 (Lp-PLA2) activity has been reported to be associated with coronary artery disease (CAD) and myocardial infarction (MI). However, whether Lp-PLA2 is a causal risk factor for CAD and MI remains unclear. Herein, we performed a two-sample mendelian randomization (MR) study to assess the causal effect of Lp-PLA2 activity on CAD and MI. MethodsWe selected 7 single-nucleotide polymorphisms (SNPs) associated with Lp-PLA2 activity as instrumental variables based on the data from Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium with 13,664 European individuals. Summary data about CAD and MI were obtained from Coronary Artery Disease Genome-wide Replication and Meta-analysis plus the Coronary Artery Disease Genetics (CARDIOGRAMPLUSC4D) consortium with 60,801 CAD cases and 43,676 MI cases (mostly European). The inverse-variance weighted method was applied to assess the causal associations of Lp-PLA2 activity with CAD and MI in the main analysis. ResultsThe main inverse-variance weighted (IVW) MR analysis showed that 1-SD increment in genetically determined LP-PLA2 activity was associated with increased risks of CAD (odds ratio, 5.93; 95% CI, 2.91–12.07; p value = 9.43 × 10-7) and MI (odds ratio, 4.71; 95% CI, 2.49–8.90; p value = 1.86 × 10-6). MR-Egger regression showed no evidence of pleiotropic bias. The causal associations were consistent in sensitivity analyses with multiple MR methods, in which showed Lp-PLA2 activity was causally associated with an increased risk of CAD and MI. ConclusionsIn this two-sample MR study, high Lp-PLA2 activity was a causal risk factor for CAD and MI, indicating that Lp-PLA2 activity may be a promising intervention target in reducing the risk of CAD and MI.

Adverse Cardiovascular Outcomes and Antihypertensive Treatment: A Genome-Wide Interaction Meta-Analysis in the International Consortium for Antihypertensive Pharmacogenomics Studies.

We sought to identify genome-wide variants influencing antihypertensive drug response and adverse cardiovascular outcomes, utilizing data from four randomized controlled trials in the International Consortium for Antihypertensive Pharmacogenomics Studies (ICAPS). Genome-wide antihypertensive drug-single nucleotide polymorphism (SNP) interaction tests for four drug classes (β-blockers, n=9,195; calcium channel blockers (CCBs), n=10,511; thiazide/thiazide-like diuretics, n=3,516; ACE-inhibitors/ARBs, n=2,559) and cardiovascular outcomes (incident myocardial infarction, stroke, or death) were analyzed among patients with hypertension of European ancestry. Top SNPs from the meta-analyses were tested for replication of cardiovascular outcomes in an independent Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) study (n=21,267), blood pressure (BP) response in independent ICAPS studies (n=1,552), and ethnic validation in African Americans from the Genetics of Hypertension Associated Treatment study (GenHAT; n=5,115). One signal reached genome-wide significance in the β-blocker-SNP interaction analysis (rs139945292, Interaction P=1.56×10-8 ). rs139945292 was validated through BP response to β-blockers, with the T-allele associated with less BP reduction (systolic BP response P=6×10-4 , Beta=3.09, diastolic BP response P=5×10-3 , Beta=1.53). The T-allele was also associated with increased adverse cardiovascular risk within the β-blocker treated patients' subgroup (P=2.35×10-4 , odds ratio=1.57, 95% confidence interval=1.23-1.99). The locus showed nominal replication in CHARGE, and consistent directional trends in β-blocker treated African Americans. rs139945292 is an expression quantitative trait locus for the 50kb upstream gene NTM (neurotrimin). No SNPs attained genome-wide significance for any other drugs classes. Top SNPs were located near CALB1 (CCB), FLJ367777 (ACE-inhibitor), and CES5AP1 (thiazide). The NTM region is associated with increased risk for adverse cardiovascular outcomes and less BP reduction in β-blocker treated patients. Further investigation into this region is warranted.

Multiethnic Genome-Wide Association Study of Subclinical Atherosclerosis in Individuals With Type 2 Diabetes.

Coronary artery calcification (CAC) and carotid artery intima-media thickness (cIMT) are measures of subclinical atherosclerosis in asymptomatic individuals and strong risk factors for cardiovascular disease. Type 2 diabetes (T2D) is an independent cardiovascular disease risk factor that accelerates atherosclerosis. We performed meta-analyses of genome-wide association studies in up to 2500 T2D individuals of European ancestry (EA) and 1590 T2D individuals of African ancestry with or without exclusion of prevalent cardiovascular disease, for CAC measured by cardiac computed tomography, and 3608 individuals of EA and 838 individuals of African ancestry with T2D for cIMT measured by ultrasonography within the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium. We replicated 2 loci (rs9369640 and rs9349379 near PHACTR1 and rs10757278 near CDKN2B) for CAC and one locus for cIMT (rs7412 and rs445925 near APOE-APOC1) that were previously reported in the general EA populations. We identified one novel CAC locus (rs8000449 near CSNK1A1L/LINC00547/POSTN at 13q13.3) at P=2.0×10-8 in EA. No additional loci were identified with the meta-analyses of EA and African ancestry. The expression quantitative trait loci analysis with nearby expressed genes derived from arterial wall and metabolic tissues from the Genotype-Tissue Expression project pinpoints POSTN, encoding a matricellular protein involved in bone formation and bone matrix organization, as the potential candidate gene at this locus. In addition, we found significant associations (P<3.1×10-4) for 3 previously reported coronary artery disease loci for these subclinical atherosclerotic phenotypes (rs2891168 near CDKN2B-AS1 and rs11170820 near FLJ12825 for CAC, and rs7412 near APOE for cIMT). Our results provide potential biological mechanisms that could link CAC and cIMT to increased cardiovascular disease risk in individuals with T2D.

24-OR: Time-to-Event GWAS for Incident Cardiovascular Disease in Type 2 Diabetes Patients

Patients with type 2 diabetes (T2D) are at two-fold increased risk of cardiovascular disease (CVD), which is the leading cause of T2D morbidity and mortality. Here, we conducted a time-to-event genome-wide association study (GWAS) to identify genetic variants associated with incident CVD among patients with T2D in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium. Incident CVD was defined based on a composite of myocardial infarction, stroke, and cardiovascular death that occurred at least one year after the diagnosis of T2D. In each participating prospective cohort, we performed GWAS using a Cox proportional hazard survival model adjusting for age, and sex to identify genetic variants associated with incident CVD, and cohort-level estimated effect sizes were combined using inverse variance weighted fixed effects meta-analysis. A total of 37,327 participants were included in the analyses (26,928 European ancestry and 10,399 non-European ancestry) which comprised 6,012 primary event cases. We identified three distinct genetic loci associated with incident CVD among individuals with T2D that reached the threshold for genome-wide significance: rs231964 (intronic variant in NOX3, hazard ratio [HR] 1.4, P=8.3x10-9), rs139753656 (intronic variant in DCC, HR 2.0, P=2.4x10-8), and rs77202398 (intronic variant in TNS3, HR 1.4, P=4.4x10-8). Among 204 known coronary artery disease risk loci, 27 were associated with incident CVD with P&amp;lt;0.05 and rs6842241 upstream of EDNRA was associated with increased risk of CVD after Bonferroni correction (HR 1.1, P=1.2x10-4). The data provide evidence of novel and known genomic regions associated with incident CVD among individuals with T2D that require validation but point to novel targets. Disclosure S. Kwak: None. P. Wu: None. J. B. Meigs: Consultant; Self; Quest Diagnostics. On behalf of the charge diabetes working group: n/a. Funding National Institutes of Health (1R01HL151855-01)

The potential shared role of inflammation in insulin resistance and schizophrenia: A bidirectional two-sample mendelian randomization study.

Insulin resistance predisposes to cardiometabolic disorders, which are commonly comorbid with schizophrenia and are key contributors to the significant excess mortality in schizophrenia. Mechanisms for the comorbidity remain unclear, but observational studies have implicated inflammation in both schizophrenia and cardiometabolic disorders separately. We aimed to examine whether there is genetic evidence that insulin resistance and 7 related cardiometabolic traits may be causally associated with schizophrenia, and whether evidence supports inflammation as a common mechanism for cardiometabolic disorders and schizophrenia. We used summary data from genome-wide association studies of mostly European adults from large consortia (Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC) featuring up to 108,557 participants; Diabetes Genetics Replication And Meta-analysis (DIAGRAM) featuring up to 435,387 participants; Global Lipids Genetics Consortium (GLGC) featuring up to 173,082 participants; Genetic Investigation of Anthropometric Traits (GIANT) featuring up to 339,224 participants; Psychiatric Genomics Consortium (PGC) featuring up to 105,318 participants; and Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium featuring up to 204,402 participants). We conducted two-sample uni- and multivariable mendelian randomization (MR) analysis to test whether (i) 10 cardiometabolic traits (fasting insulin, high-density lipoprotein and triglycerides representing an insulin resistance phenotype, and 7 related cardiometabolic traits: low-density lipoprotein, fasting plasma glucose, glycated haemoglobin, leptin, body mass index, glucose tolerance, and type 2 diabetes) could be causally associated with schizophrenia; and (ii) inflammation could be a shared mechanism for these phenotypes. We conducted a detailed set of sensitivity analyses to test the assumptions for a valid MR analysis. We did not find statistically significant evidence in support of a causal relationship between cardiometabolic traits and schizophrenia, or vice versa. However, we report that a genetically predicted inflammation-related insulin resistance phenotype (raised fasting insulin (raised fasting insulin (Wald ratio OR = 2.95, 95% C.I, 1.38-6.34, Holm-Bonferroni corrected p-value (p) = 0.035) and lower high-density lipoprotein (Wald ratio OR = 0.55, 95% C.I., 0.36-0.84; p = 0.035)) was associated with schizophrenia. Evidence for these associations attenuated to the null in multivariable MR analyses after adjusting for C-reactive protein, an archetypal inflammatory marker: (fasting insulin Wald ratio OR = 1.02, 95% C.I, 0.37-2.78, p = 0.975), high-density lipoprotein (Wald ratio OR = 1.00, 95% C.I., 0.85-1.16; p = 0.849), suggesting that the associations could be fully explained by inflammation. One potential limitation of the study is that the full range of gene products from the genetic variants we used as proxies for the exposures is unknown, and so we are unable to comment on potential biological mechanisms of association other than inflammation, which may also be relevant. Our findings support a role for inflammation as a common cause for insulin resistance and schizophrenia, which may at least partly explain why the traits commonly co-occur in clinical practice. Inflammation and immune pathways may represent novel therapeutic targets for the prevention or treatment of schizophrenia and comorbid insulin resistance. Future work is needed to understand how inflammation may contribute to the risk of schizophrenia and insulin resistance.

Concordance rate in cattle and sheep between genotypes differing in Illumina GenCall quality score.

Proper quality control of data prior to downstream analyses is fundamental to ensure integrity of results; quality control of genomic data is no exception. While many metrics of quality control of genomic data exist, the objective of the present study was to quantify the genotype and allele concordance rate between called single nucleotide polymorphism (SNP) genotypes differing in GenCall (GC) score; the GC score is a confidence measure assigned to each Illumina genotype call. This objective was achieved using Illumina beadchip genotype data from 771 cattle (12428767 genotypes in total post-editing) and 80 sheep (1557360 SNPs genotypes in total post-editing) each genotyped in duplicate. The called genotype with the lowest associated GC score was compared to the genotype called for the same SNP in the same duplicated animal sample but with a GC score of >0.90 (assumed to represent the true genotype). The mean genotype concordance rate for a GC score of <0.300, 0.300-0.549, and ≥0.550 in the cattle (sheep in parenthesis) was 0.9467 (0.9864), 0.9707 (0.9953), and 0.9994 (0.99997) respectively; the respective allele concordance rate was 0.9730 (0.9930), 0.9849 (0.9976), and 0.9997 (0.99998). Hence, concordance eroded as the GC score of the called genotype reduced, albeit the impact was not dramatic and was not very noticeable until a GC score of <0.55. Moreover, the impact was greater and more consistent in the cattle population than in the sheep population. Furthermore, an impact of GC score on genotype concordance rate existed even for the same SNP GenTrain value; the GenTrain value is a statistical score that depicts the shape of the genotype clusters and the relative distance between the called genotype clusters.

NIA genetics of Alzheimer’s disease data storage site (NIAGADS): Update 2020

AbstractBackgroundNIAGADS is a national genetics data repository that facilitates access of genotypic data to qualified investigators for the study of the genetics of late‐onset Alzheimer’s disease (AD) and other neurological diseases. Collaborations with large consortia and centers such as the Alzheimer’s Disease Genetics Consortium (ADGC), Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium, the Alzheimer’s Disease Genome Sequencing Project (ADSP), and the Genome Center for Alzheimer’s Disease (GCAD) allow NIAGADS to lead the effort in managing large AD datasets that can be easily accessed by the research community and utilized to their fullest extent.MethodNIAGADS is supported by National Institute on Aging (NIA) under a cooperative agreement (U24 AG041689). All data derived from NIA funded AD genetics studies are expected to be deposited in NIAGADS or another NIA approved site. NIAGADS manages a Data Sharing Service (DSS) that facilitates the deposition and sharing of genomic data and association results with approved users in the neurodegenerative research community. In addition, researchers are able to freely use the NIAGADS Genomics Database to search annotation resources that link published AD studies to AD‐relevant sequence features and genome‐wide annotations.ResultAs of January 2020, NIAGADS houses 67 datasets (23 added in 2019) with &gt;59,000 samples and nearly 34 billion genotypes. Qualified investigators can retrieve ADSP sequencing data with ease and flexibility through the NIAGADS DSS. The ADSP and other contributing studies have completed whole exome sequencing (WES) of 20,630 subjects and whole‐genome sequencing (WGS) of 4,750 subjects. Raw WES and WGS files, quality controlled VCF files, and phenotype data files are available via qualified access. The next planned dataset release will occur in late 2020 and will contain an additional 13,136 genomes jointly genotype called with the first release of 4,750 genomes, totaling about 17,886 genomes.ConclusionNIAGADS is a rich resource for AD researchers, with the goal of facilitating advances in Alzheimer’s genetics research. By housing datasets from multiple projects and institutions, NIAGADS enables AD researchers to be more efficient in meeting their research goals. Datasets, guidelines, and new features are available on our website at https://www.niagads.org.