Objective Genome‐wide association studies (GWAS) have been successful at identifying associations with stroke and stroke subtypes, but have not yet identified any associations solely with small vessel stroke (SVS). SVS comprises one quarter of all ischemic stroke and is a major manifestation of cerebral small vessel disease, the primary cause of vascular cognitive impairment. Studies across neurological traits have shown that younger‐onset cases have an increased genetic burden. We leveraged this increased genetic burden by performing an age‐at‐onset informed GWAS meta‐analysis, including a large younger‐onset SVS population, to identify novel associations with stroke. Methods We used a three‐stage age‐at‐onset informed GWAS to identify novel genetic variants associated with stroke. On identifying a novel locus associated with SVS, we assessed its influence on other small vessel disease phenotypes, as well as on messenger RNA (mRNA) expression of nearby genes, and on DNA methylation of nearby CpG sites in whole blood and in the fetal brain. Results We identified an association with SVS in 4,203 cases and 50,728 controls on chromosome 16q24.2 (odds ratio [OR; 95% confidence interval {CI}] = 1.16 [1.10–1.22]; p = 3.2 × 10 −9 ). The lead single‐nucleotide polymorphism (rs12445022) was also associated with cerebral white matter hyperintensities (OR [95% CI] = 1.10 [1.05–1.16]; p = 5.3 × 10 −5 ; N = 3,670), but not intracerebral hemorrhage (OR [95% CI] = 0.97 [0.84–1.12]; p = 0.71; 1,545 cases, 1,481 controls). rs12445022 is associated with mRNA expression of ZCCHC14 in arterial tissues ( p = 9.4 × 10 −7 ) and DNA methylation at probe cg16596957 in whole blood ( p = 5.3 × 10 −6 ). Interpretation 16q24.2 is associated with SVS. Associations of the locus with expression of ZCCHC14 and DNA methylation suggest the locus acts through changes to regulatory elements. Ann Neurol 2017;81:383–394
SOS2 and ACP1 Loci Identified through Large-Scale Exome Chip Analysis Regulate Kidney Development and Function
Genome-wide association studies have identified >50 common variants associated with kidney function, but these variants do not fully explain the variation in eGFR. We performed a two-stage meta-analysis of associations between genotypes from the Illumina exome array and eGFR on the basis of serum creatinine (eGFRcrea) among participants of European ancestry from the CKDGen Consortium ( n Stage1 : 111,666; n Stage2 : 48,343). In single-variant analyses, we identified single nucleotide polymorphisms at seven new loci associated with eGFRcrea ( PPM1J , EDEM3, ACP1, SPEG, EYA4, CYP1A1 , and ATXN2L ; P Stage1 <3.7×10 −7 ), of which most were common and annotated as nonsynonymous variants. Gene-based analysis identified associations of functional rare variants in three genes with eGFRcrea, including a novel association with the SOS Ras/Rho guanine nucleotide exchange factor 2 gene, SOS2 ( P =5.4×10 −8 by sequence kernel association test). Experimental follow-up in zebrafish embryos revealed changes in glomerular gene expression and renal tubule morphology in the embryonic kidney of acp1- and sos2 -knockdowns. These developmental abnormalities associated with altered blood clearance rate and heightened prevalence of edema. This study expands the number of loci associated with kidney function and identifies novel genes with potential roles in kidney formation.
FTS3‐01‐02: Epidemiology of Vascular Related Risk Factors for Dementia
AbstractBackgroundPlasma amyloid‐β (Aβ) peptide levels have been examined as a low‐cost accessible marker for risk of incident Alzheimer's disease (AD) and dementia, but results have varied between studies. We reassessed these associations in one of the largest, prospective, community‐based studies to date.MethodsA total of 2189 dementia‐free, Framingham Study participants aged >60 years (mean age, 72 ± 8 years; 56% women) had plasma Aβ1‐42 and Aβ1‐40 measured and were followed prospectively (mean, 7.6 ± 3.0 years) for dementia/AD.ResultsIncreased plasma Aβ1‐42 levels were associated with lower risk of dementia (Aβ1‐42: hazard ratio [HR] = 0.80 [0.71‒0.90], P < .001; Aβ1‐42‐to‐Aβ1‐40 ratio: HR = 0.86 [0.76‒0.98], P = .027) and AD (Aβ1‐42: HR = 0.79 [0.69‒0.90], P < .001; Aβ1‐42‐to‐Aβ1‐40 ratio: HR = 0.83 [0.72‒0.96], P = .012).ConclusionOur results suggest that lower plasma Aβ levels are associated with risk of incident AD and dementia. They encourage further evaluation of plasma Aβ levels as a biomarker for risk of developing clinical AD and dementia.
O4‐04‐05: ASSOCIATION OF ALZHEIMER DISEASE GWAS LOCI WITH MRI‐MARKERS OF BRAIN AGING
Genetic College Many genomic elements in humans are associated with behavior, including educational attainment. In a genome-wide association study including more than 100,000 samples, Rietveld et al. (p. 1467 , published online 30 May; see the Perspective by Flint and Munafò ) looked for genes related to educational attainment in Caucasians. Small genetic effects at three loci appeared to impact educational attainment.
Simple Risk Model Predicts Incidence of Atrial Fibrillation in a Racially and Geographically Diverse Population: the CHARGE‐AF Consortium
Background Tools for the prediction of atrial fibrillation ( AF ) may identify high‐risk individuals more likely to benefit from preventive interventions and serve as a benchmark to test novel putative risk factors. Methods and Results Individual‐level data from 3 large cohorts in the U nited S tates (Atherosclerosis Risk in Communities [ ARIC ] study, the Cardiovascular Health Study [ CHS ], and the Framingham Heart Study [ FHS ]), including 18 556 men and women aged 46 to 94 years (19% A frican A mericans, 81% whites) were pooled to derive predictive models for AF using clinical variables. Validation of the derived models was performed in 7672 participants from the Age, Gene and Environment—Reykjavik study ( AGES ) and the Rotterdam Study ( RS ). The analysis included 1186 incident AF cases in the derivation cohorts and 585 in the validation cohorts. A simple 5‐year predictive model including the variables age, race, height, weight, systolic and diastolic blood pressure, current smoking, use of antihypertensive medication, diabetes, and history of myocardial infarction and heart failure had good discrimination (C‐statistic, 0.765; 95% CI , 0.748 to 0.781). Addition of variables from the electrocardiogram did not improve the overall model discrimination (C‐statistic, 0.767; 95% CI , 0.750 to 0.783; categorical net reclassification improvement, −0.0032; 95% CI , −0.0178 to 0.0113). In the validation cohorts, discrimination was acceptable ( AGES C‐statistic, 0.664; 95% CI , 0.632 to 0.697 and RS C‐statistic, 0.705; 95% CI , 0.664 to 0.747) and calibration was adequate. Conclusion A risk model including variables readily available in primary care settings adequately predicted AF in diverse populations from the U nited S tates and E urope.
Integration of genome-wide association studies with biological knowledge identifies six novel genes related to kidney function