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We examined associations of an Alzheimer's disease (AD) Genetic Risk Score (AD‐GRS) and midlife cognitive and neuroimaging outcomes in 1,252 middle‐aged participants (311 with brain MRI). A higher AD‐GRS based on 25 previously identified loci (excluding apolipoprotein E [APOE]) was associated with worse Montreal Cognitive Assessment (−0.14 standard deviation [SD] [95% confidence interval {CI}: ‐0.26, −0.02]), older machine learning predicted brain age (2.35 years[95%CI: 0.01, 4.69]), and white matter hyperintensity volume (0.35 SD [95% CI: 0.00, 0.71]), but not with a composite cognitive outcome, total brain, or hippocampal volume. APOE ε4 allele was not associated with any outcomes. AD risk genes beyond APOE may contribute to subclinical differences in cognition and brain health in midlife. ANN NEUROL 2023;93:629–634 [ABSTRACT FROM AUTHOR]

During aging, intracranial volume remains unchanged and represents maximally attained brain size, while various interacting biological phenomena lead to brain volume loss. Consequently, intracranial volume and brain volume in late life reflect different genetic influences. Our genome-wide association study (GWAS) in 8,175 community-dwelling elderly persons did not reveal any associations at genome-wide significance (P < 5 × 10?8) for brain volume. In contrast, intracranial volume was significantly associated with two loci: rs4273712 (P = 3.4 × 10?11), a known height-associated locus on chromosome 6q22, and rs9915547 (P = 1.5 × 10?12), localized to the inversion on chromosome 17q21. We replicated the associations of these loci with intracranial volume in a separate sample of 1,752 elderly persons (P = 1.1 × 10?3 for 6q22 and 1.2 × 10?3 for 17q21). Furthermore, we also found suggestive associations of the 17q21 locus with head circumference in 10,768 children (mean age of 14.5 months). Our data identify two loci associated with head size, with the inversion at 17q21 also likely to be involved in attaining maximal brain size. [ABSTRACT FROM AUTHOR]

Background: Microarray technology provides an efficient means for globally exploring physiological processes governed by the coordinated expression of multiple genes. However, identification of genes differentially expressed in microarray experiments is challenging because of their potentially high type I error rate. Methods for large-scale statistical analyses have been developed but most of them are applicable to two-sample or two-condition data. Results: We developed a large-scale multiple-group F-test based method, named ranking analysis of F-statistics (RAF), which is an extension of ranking analysis of microarray data (RAM) for two-sample t-test. In this method, we proposed a novel random splitting approach to generate the null distribution instead of using permutation, which may not be appropriate for microarray data. We also implemented a two-simulation strategy to estimate the false discovery rate. Simulation results suggested that it has higher efficiency in finding differentially expressed genes among multiple classes at a lower false discovery rate than some commonly used methods. By applying our method to the experimental data, we found 107 genes having significantly differential expressions among 4 treatments at <0.7% FDR, of which 31 belong to the expressed sequence tags (ESTs), 76 are unique genes who have known functions in the brain or central nervous system and belong to six major functional groups. Conclusion: Our method is suitable to identify differentially expressed genes among multiple groups, in particular, when sample size is small. [ABSTRACT FROM AUTHOR]

It is becoming clear that the etiology of complex diseases involves not only genetic and environmental factors but also gene–environment (GE) interactions. Therefore, it is important to take account of all these factors to improve the power of an epidemiological study design. We propose here a novel parent–child pair (PCP) design for this purpose. In comparison with conventional designs, this approach has the following advantages: (a) PCP is a 4 × 16 design consisting of pairs of parent–child (PC) genotype statuses, PC exposure statuses and PC disease statuses. Therefore, it utilizes more information than the traditional approaches in association studies; (b) It can determine whether findings in studies of association between disease and genetic or environmental factors and their interaction are spurious, arising from Hardy–Weinberg disequilibrium or the other factors; (c) Since the information from both parents and children of the PC pairs are used in this design, it has high power for detecting association of candidate gene, exposure with a complex disease and GE interaction. We also present a set of estimates of relative risks of candidate genes, exposures and GE interactions under the multiplicative model and a method for computing the sample size requirements to test for these relative risks in the context of the PCP design. [ABSTRACT FROM AUTHOR]

Abstract: We have previously reported that L5, the most negatively charged subfraction of plasma low-density lipoprotein (LDL), induces mononuclear leukocyte (MNC) adhesion under flow conditions in vitro when endothelial cells are incubated with L5. The present study was undertaken to identify responsible adhesion molecules and chemokines. LDL isolated from patients with homozygous familial hypercholesterolemia was separated into five distinct subfractions by high-capacity ion-exchange chromatography. Differentially expressed mRNA between human umbilical vein endothelial cells (HUVEC) incubated (for 22h) with the earliest subfraction (L1: 20μg/ml) and the latest and most negatively charged subfraction (L5: 20μg/ml) was identified by DNA microarray analysis using three independent sets of RNA. mRNA consistently upregulated by L5 included VCAM-1 (2.3-fold) and CXC chemokines GRO-α (2.3), GRO-β (4.6), IL-8 (2.5), ENA-78 (2.3), GRO-γ (1.6) and GCP-2 (1.5). These results were validated by Northern analysis, semi-quantitative RT-PCR or ELISA. Blocking studies using monoclonal antibodies revealed that both primary capture and stable adhesion of MNC to HUVEC and human aortic endothelial cells (HAEC) incubated with L5 was mediated by VCAM-l/α4 integrin, whereas GRO and its receptor CXCR2 were involved in the stable adhesion of MNC to L5-treated HAEC. [Copyright &y& Elsevier]

Susceptibility to ischemic damage to the subcortical white matter of the brain has a strong genetic basis. Dysregulation of matrix metalloproteinases (MMPs) contributes to loss of cerebrovascular integrity and white matter injury. We investigated whether sequence variation in the genes encoding MMP3 and MMP9 is associated with variation in leukoaraiosis volume, determined by magnetic resonance imaging, in non-Hispanic whites and African-Americans using family-based association tests. Seven hundred and fifty-six white and 671 African-American individuals from sibships ascertained through two or more siblings with hypertension were genotyped for 7 and 8 haplotype-tagging polymorphisms in the MMP3 and MMP9 genes, respectively. MMP3 sequence variation was significantly associated with variation in leukoaraiosis volume in Whites. Two common haplotypes with opposing relationships to leukoaraiosis volume were identified. MMP9 sequence variation was also significantly associated with variation in leukoaraiosis volume in both African-Americans and Whites. Different haplotypes contributed to these associations in the two racial groups. These findings add to the growing body of evidence from animal models and human clinical studies suggesting a role of MMPs in ischemic white matter injury. They provide the basis for further investigation of the role of these genes in susceptibility and/or progression to clinical disease. [ABSTRACT FROM AUTHOR]

Abstract: Microarray technology provides a powerful tool for the expression profile of thousands of genes simultaneously, which makes it possible to explore the molecular and metabolic etiology of the development of a complex disease under study. However, classical statistical methods and technologies fail to be applicable to microarray data. Therefore, it is necessary and motivating to develop powerful methods for large-scale statistical analyses. In this paper, we described a novel method, called Ranking Analysis of Microarray Data (RAM). RAM, which is a large-scale two-sample t-test method, is based on comparisons between a set of ranked T statistics and a set of ranked Z values (a set of ranked estimated null scores) yielded by a “randomly splitting” approach instead of a “permutation” approach and a two-simulation strategy for estimating the proportion of genes identified by chance, i.e., the false discovery rate (FDR). The results obtained from the simulated and observed microarray data show that RAM is more efficient in identification of genes differentially expressed and estimation of FDR under undesirable conditions such as a large fudge factor, small sample size, or mixture distribution of noises than Significance Analysis of Microarrays. [Copyright &y& Elsevier]

Neurofilament light chain (NfL) levels in circulation have been established as a sensitive biomarker of neuro-axonal damage across a range of neurodegenerative disorders. Elucidation of the genetic architecture of blood NfL levels could provide new insights into molecular mechanisms underlying neurodegenerative disorders. In this meta-analysis of genome-wide association studies (GWAS) of blood NfL levels from eleven cohorts of European ancestry, we identify two genome-wide significant loci at 16p12 (UMOD) and 17q24 (SLC39A11). We observe association of three loci at 1q43 (FMN2), 12q14, and 12q21 with blood NfL levels in the meta-analysis of African-American ancestry. In the trans-ethnic meta-analysis, we identify three additional genome-wide significant loci at 1p32 (FGGY), 6q14 (TBX18), and 4q21. In the post-GWAS analyses, we observe the association of higher NfL polygenic risk score with increased plasma levels of total-tau, Aβ-40, Aβ-42, and higher incidence of Alzheimer's disease in the Rotterdam Study. Furthermore, Mendelian randomization analysis results suggest that a lower kidney function could cause higher blood NfL levels. This study uncovers multiple genetic loci of blood NfL levels, highlighting the genes related to molecular mechanism of neurodegeneration. An ancestry-specific and trans-ethnic meta-analysis of Genome-wide Association Study of blood NfL levels identified multiple loci related to neurodegeneration and potential causal association between reduced kidney function and higher blood NfL levels. [ABSTRACT FROM AUTHOR]

Understanding the genetic architecture of brain structure is challenging, partly due to difficulties in designing robust, non-biased descriptors of brain morphology. Until recently, brain measures for genome-wide association studies (GWAS) consisted of traditionally expert-defined or software-derived image-derived phenotypes (IDPs) that are often based on theoretical preconceptions or computed from limited amounts of data. Here, we present an approach to derive brain imaging phenotypes using unsupervised deep representation learning. We train a 3-D convolutional autoencoder model with reconstruction loss on 6130 UK Biobank (UKBB) participants' T1 or T2-FLAIR (T2) brain MRIs to create a 128-dimensional representation known as Unsupervised Deep learning derived Imaging Phenotypes (UDIPs). GWAS of these UDIPs in held-out UKBB subjects (n = 22,880 discovery and n = 12,359/11,265 replication cohorts for T1/T2) identified 9457 significant SNPs organized into 97 independent genetic loci of which 60 loci were replicated. Twenty-six loci were not reported in earlier T1 and T2 IDP-based UK Biobank GWAS. We developed a perturbation-based decoder interpretation approach to show that these loci are associated with UDIPs mapped to multiple relevant brain regions. Our results established unsupervised deep learning can derive robust, unbiased, heritable, and interpretable brain imaging phenotypes. A study utilizing unsupervised deep learning to generate interpretable brain imaging phenotypes from brain T1 and T2-FLAIR MRI identified 97 genetic loci enhancing understanding of brain structure genetics. [ABSTRACT FROM AUTHOR]

The heritability explained by local ancestry markers in an admixed population (h γ 2) provides crucial insight into the genetic architecture of a complex disease or trait. Estimation of h γ 2 can be susceptible to biases due to population structure in ancestral populations. Here, we present heritability estimation from admixture mapping summary statistics (HAMSTA), an approach that uses summary statistics from admixture mapping to infer heritability explained by local ancestry while adjusting for biases due to ancestral stratification. Through extensive simulations, we demonstrate that HAMSTA h γ 2 estimates are approximately unbiased and are robust to ancestral stratification compared to existing approaches. In the presence of ancestral stratification, we show a HAMSTA-derived sampling scheme provides a calibrated family-wise error rate (FWER) of ∼5% for admixture mapping, unlike existing FWER estimation approaches. We apply HAMSTA to 20 quantitative phenotypes of up to 15,988 self-reported African American individuals in the Population Architecture using Genomics and Epidemiology (PAGE) study. We observe h ˆ γ 2 in the 20 phenotypes range from 0.0025 to 0.033 (mean h ˆ γ 2 = 0.012 ± 9.2 × 10−4), which translates to h ˆ 2 ranging from 0.062 to 0.85 (mean h ˆ 2 = 0.30 ± 0.023). Across these phenotypes we find little evidence of inflation due to ancestral population stratification in current admixture mapping studies (mean inflation factor of 0.99 ± 0.001). Overall, HAMSTA provides a fast and powerful approach to estimate genome-wide heritability and evaluate biases in test statistics of admixture mapping studies. This study reports a method to estimate heritability explained by local ancestry using admixture mapping summary statistics and evaluates potential biases in admixture mapping. The method provides a strategy for summary statistic-based heritability estimation in admixed populations and controlling false positives due to ancestral population stratification in admixture mapping studies. [ABSTRACT FROM AUTHOR]

Long non-coding RNAs (lncRNAs) are known to perform important regulatory functions in lipid metabolism. Large-scale whole-genome sequencing (WGS) studies and new statistical methods for variant set tests now provide an opportunity to assess more associations between rare variants in lncRNA genes and complex traits across the genome. In this study, we used high-coverage WGS from 66,329 participants of diverse ancestries with measurement of blood lipids and lipoproteins (LDL-C, HDL-C, TC, and TG) in the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) program to investigate the role of lncRNAs in lipid variability. We aggregated rare variants for 165,375 lncRNA genes based on their genomic locations and conducted rare-variant aggregate association tests using the STAAR (variant-set test for association using annotation information) framework. We performed STAAR conditional analysis adjusting for common variants in known lipid GWAS loci and rare-coding variants in nearby protein-coding genes. Our analyses revealed 83 rare lncRNA variant sets significantly associated with blood lipid levels, all of which were located in known lipid GWAS loci (in a ±500-kb window of a Global Lipids Genetics Consortium index variant). Notably, 61 out of 83 signals (73%) were conditionally independent of common regulatory variation and rare protein-coding variation at the same loci. We replicated 34 out of 61 (56%) conditionally independent associations using the independent UK Biobank WGS data. Our results expand the genetic architecture of blood lipids to rare variants in lncRNAs. Wang and colleagues conducted rare-variant association analyses of long non-coding RNAs (lncRNAs) in 66,000 ancestrally diverse TOPMed participants with whole-genome sequencing and measurements of blood lipids and lipoproteins. The findings suggest an additional genomic element in known lipid gene regions that is distinct from the known lipid-associated genes. [ABSTRACT FROM AUTHOR]

Introduction: Polygenic Risk Scores (PRSs) are summaries of genetic risk alleles for an outcome. Methods: We used summary statistics from five GWASs of AD to construct PRSs in 4,189 diverse Hispanics/Latinos (mean age 63 years) from the Study of Latinos-Investigation of Neurocognitive Aging (SOL-INCA). We assessed the PRS associations with MCI in the combined set of people and in diverse subgroups, and when including and excluding the APOE gene region. We also assessed PRS associations with MCI in an independent dataset from the Mass General Brigham Biobank. Results: A simple sum of 5 PRSs ("PRSsum"), each constructed based on a different AD GWAS, was associated with MCI (OR = 1.28, 95% CI [1.14, 1.41]) in a model adjusted for counts of the APOE- ϵ 2 and APOE- ϵ 4 alleles. Associations of single-GWAS PRSs were weaker. When removing SNPs from the APOE region from the PRSs, the association of PRSsum with MCI was weaker (OR = 1.17, 95% CI [1.04,1.31] with adjustment for APOE alleles). In all association analyses, APOE- ϵ 4 and APOE- ϵ 2 alleles were not associated with MCI. Discussion: A sum of AD PRSs is associated with MCI in Hispanic/Latino older adults. Despite no association of APOE- ϵ 4 and APOE- ϵ 2 alleles with MCI, the association of the AD PRS with MCI is stronger when including the APOE region. Thus, APOE variants different than the classic APOE alleles may be important predictors of MCI in Hispanic/Latino adults. [ABSTRACT FROM AUTHOR]

Exonic variants present some of the strongest links between genotype and phenotype. However, these variants can have significant inter-individual pathogenicity differences, known as variable penetrance. In this study, we propose a model where genetically controlled mRNA splicing modulates the pathogenicity of exonic variants. By first cataloging exonic inclusion from RNA-sequencing data in GTEx V8, we find that pathogenic alleles are depleted on highly included exons. Using a large-scale phased whole genome sequencing data from the TOPMed consortium, we observe that this effect may be driven by common splice-regulatory genetic variants, and that natural selection acts on haplotype configurations that reduce the transcript inclusion of putatively pathogenic variants, especially when limiting to haploinsufficient genes. Finally, we test if this effect may be relevant for autism risk using families from the Simons Simplex Collection, but find that splicing of pathogenic alleles has a penetrance reducing effect here as well. Overall, our results indicate that common spliceregulatory variants may play a role in reducing the damaging effects of rare exonic variants. [ABSTRACT FROM AUTHOR]

The predictive ability of coronary heart disease (CHD) and ischemic stroke (IS) polygenic risk scores (PRS) have been evaluated individually, but whether they predict the combined outcome of atherosclerotic cardiovascular disease (ASCVD) remains insufficiently researched. It is also unclear whether associations of the CHD and IS PRS with ASCVD are independent of subclinical atherosclerosis measures. 7,286 White and 2,016 Black participants from the population-based Atherosclerosis Risk in Communities study who were free of cardiovascular disease and type 2 diabetes at baseline were included. We computed previously validated CHD and IS PRS consisting of 1,745,179 and 3,225,583 genetic variants, respectively. Cox proportional hazards models were used to test the association between each PRS and ASCVD, adjusting for traditional risk factors, ankle-brachial index, carotid intima media thickness, and carotid plaque. The hazard ratios (HR) for the CHD and IS PRS were significant with HR of 1.50 (95% CI: 1.36–1.66) and 1.31 (95% CI: 1.18–1.45) respectively for the risk of incident ASCVD per standard deviation increase in CHD and IS PRS among White participants after adjusting for traditional risk factors. The HR for the CHD PRS was not significant with an HR of 0.95 (95% CI: 0.79–1.13) for the risk of incident ASCVD in Black participants. The HR for the IS PRS was significant with an HR of 1.26 (95%CI: 1.05–1.51) for the risk of incident ASCVD in Black participants. The association of the CHD and IS PRS with ASCVD was not attenuated in White participants after adjustment for ankle-brachial index, carotid intima media thickness, and carotid plaque. The CHD and IS PRS do not cross-predict well, and predict better the outcome for which they were created than the composite ASCVD outcome. Thus, the use of the composite outcome of ASCVD may not be ideal for genetic risk prediction. [ABSTRACT FROM AUTHOR]

A correction to the article "Common variants at 6q22 and 17q21 are associated with intracranial volume," that appeared in the April 15, 2012 is presented.

Background: Studies of adiposity and brain pathology in African Americans (AA) are sparse despite higher rates of obesity, dementia, and dementia-associated brain pathology in AA. This study examined relations of adiposity to white matter hyperintensities (WMH) and total brain volume (TBV) in AA and non-Hispanic whites (NHW).Methods: Waist circumference (WC) and body mass index (BMI) were measured in the Genetic Epidemiology Network of Arteriopathy study at Visits 1 (mean age 57 [±11]) and 2 (mean age 61 [±10], mean 5.2 years later). Brain MRIs were obtained shortly after Visit 2 in 1,702 participants (64% women, 48% AA). Multilevel linear regression using generalized estimating equation estimated associations of adiposity (cross-sectional) or adiposity changes with WMH (accounting for intracranial size) or TBV adjusting for demographics, cardiovascular risk factors, and incorporating adiposity-by-race interactions. Adiposity-by-age interactions were examined.Results: Concurrent TBV was inversely associated with BMI (β = -2.76 [95% confidence interval (CI): -4.99, -0.53]) and WC (β = -2.19 [CI: -4.04, -0.34]). Concurrent WMH were negatively associated with BMI (β = -0.04 [CI: -0.06, -0.01]) and, among NHW, with WC (β = -0.04 [CI: -0.06, -0.02]) but not with changes in BMI or WC. BMI increases were associated with lower TBV (β = -16.20, [CI: -30.34, -2.06]) in AA but not in NHW (β = -2.76 [CI: -14.02, 8.51]), although race-by-adiposity interactions were not supported. WC increases were not associated with MRI outcomes.Conclusion: Greater measures of obesity and increases in measures of obesity, which are common in mid-life, could be detrimental to brain health, particularly in AA. [ABSTRACT FROM AUTHOR]

Footnotes 1 Nonstandard Abbreviations and Acronyms CHD coronary heart disease FH familial hypercholesterolemia LDL-C low-density lipoprotein cholesterol 2 S.D. de Ferranti and A.E. Moran contributed equally. Keywords: cardiovascular disease; familial hypercholesterolemia; genotype; low-density lipoprotein cholesterol; phenotype EN cardiovascular disease familial hypercholesterolemia genotype low-density lipoprotein cholesterol phenotype 1556 1559 4 05/15/23 20230516 NES 230516 Familial hypercholesterolemia (FH) is a genetic disorder characterized by markedly elevated low-density lipoprotein cholesterol (LDL-C) from birth that often causes premature coronary heart disease (CHD).[1] FH can be diagnosed with established clinical criteria such as the Dutch Lipid Clinic Network criteria with or without genetic testing.[1] This study aimed to quantify the risks for incident CHD events associated with severe hypercholesterolemia (LDL-C >=190 mg/dL) with or without an FH genotype. APOB indicates apolipoprotein B; CHD, coronary heart disease; FH, familial hypercholesterolemia; LDL-C, low-density lipoprotein cholesterol; LDLR, low-density lipoprotein receptor; and PCSK9: proprotein convertase subtilisin/kexin type 9. [Extracted from the article]

APOE-ɛ4 risk on Mild Cognitive Impairment (MCI) and Alzheimer's Disease (AD) differs between race/ethnic groups, presumably due to ancestral genomic background surrounding the APOE locus. We studied whether African and Amerindian ancestry-enriched genetic variants in the APOE region modify the effect of the APOE-ɛ4 alleles on Mild Cognitive Impairment (MCI) in Hispanics/Latinos. We defined African and Amerindian ancestry-enriched variants as those common in one Hispanic/Latino parental ancestry and rare in the other two. We identified such variants in the APOE region with a predicted moderate impact based on the SnpEff tool. We tested their interaction with APOE-ɛ4 on MCI in the Study of Latinos-Investigation of Neurocognitive Aging (SOL-INCA) population and African Americans from the Atherosclerosis Risk In Communities (ARIC) study. We identified 5 Amerindian and 14 African enriched variants with an expected moderate effect. A suggestive significant interaction (p-value = 0.01) was found for one African-enriched variant, rs8112679, located in the ZNF222 gene fourth exon. Our results suggest there are no ancestry-enriched variants with large effect sizes of interaction effects with APOE-ɛ4 on MCI in the APOE region in the Hispanic/Latino population. Further studies are needed in larger datasets to identify potential interactions with smaller effect sizes. [ABSTRACT FROM AUTHOR]

Background: Thyroid hormones play a key role in differentiation and metabolism and are known regulators of gene expression through both genomic and epigenetic processes including DNA methylation. The aim of this study was to examine associations between thyroid hormones and DNA methylation. Methods: We carried out a fixed-effect meta-analysis of epigenome-wide association study (EWAS) of blood DNA methylation sites from 8 cohorts from the ThyroidOmics Consortium, incorporating up to 7073 participants of both European and African ancestry, implementing a discovery and replication stage. Statistical analyses were conducted using normalized beta CpG values as dependent and log-transformed thyrotropin (TSH), free thyroxine, and free triiodothyronine levels, respectively, as independent variable in a linear model. The replicated findings were correlated with gene expression levels in whole blood and tested for causal influence of TSH and free thyroxine by two-sample Mendelian randomization (MR). Results: Epigenome-wide significant associations (p-value <1.1E-7) of three CpGs for free thyroxine, five for free triiodothyronine, and two for TSH concentrations were discovered and replicated (combined p-values = 1.5E-9 to 4.3E-28). The associations included CpG sites annotated to KLF9 (cg00049440) and DOT1L (cg04173586) that overlap with all three traits, consistent with hypothalamic–pituitary–thyroid axis physiology. Significant associations were also found for CpGs in FKBP5 for free thyroxine, and at CSNK1D/LINCO1970 and LRRC8D for free triiodothyronine. MR analyses supported a causal effect of thyroid status on DNA methylation of KLF9. DNA methylation of cg00049440 in KLF9 was inversely correlated with KLF9 gene expression in blood. The CpG at CSNK1D/LINC01970 overlapped with thyroid hormone receptor alpha binding peaks in liver cells. The total additive heritability of the methylation levels of the six significant CpG sites was between 25% and 57%. Significant methylation QTLs were identified for CpGs at KLF9, FKBP5, LRRC8D, and CSNK1D/LINC01970. Conclusions: We report novel associations between TSH, thyroid hormones, and blood-based DNA methylation. This study advances our understanding of thyroid hormone action particularly related to KLF9 and serves as a proof-of-concept that integrations of EWAS with other -omics data can provide a valuable tool for unraveling thyroid hormone signaling in humans by complementing and feeding classical in vitro and animal studies. [ABSTRACT FROM AUTHOR]

A correction to the article "Common variants at 6q22 and 17q21 are associated with intracranial volume" that was published in the April 15, 2012 online issue is presented.

Recent genome wide association studies have identified 89 common genetic variants robustly associated with ischemic stroke and primarily located in non-coding regions. To evaluate the contribution of coding variants, which are mostly rare, we performed an exome array analysis on 106,101 SNPs for 9721 ischemic stroke cases from the SiGN Consortium, and 12,345 subjects with no history of stroke from the Health Retirement Study and SiGN consortium. We identified 15 coding variants significantly associated with all ischemic stroke at array-wide threshold (i.e., p < 4.7 × 10−7), including two common SNPs in ABO that have previously been associated with stroke. Twelve of the remaining 13 variants were extremely rare in European Caucasians (MAF < 0.1%) and the associations were driven by African American samples. There was no evidence for replication of these associations in either TOPMed Stroke samples (n = 5613 cases) or UK Biobank (n = 5874 stroke cases), although power to replicate was very low given the low allele frequencies of the associated variants and a shortage of samples from diverse ancestries. Our study highlights the need for acquiring large, well-powered diverse cohorts to study rare variants, and the technical challenges using array-based genotyping technologies for rare variant genotyping. [ABSTRACT FROM AUTHOR]

Background: Whether diabetes and adipokine‐driven inflammation explain the association of obesity to cognitive impairment is unknown. Methods: Structural equation models estimated the total effects of waist circumference on cognitive outcomes among African American participants cross‐sectionally (index exam) and longitudinally. Total effects were deconstructed into direct pathways of waist circumference to cognitive impairment and indirect mediation pathways through leptin, soluble tumor necrosis factor receptor 2 (sTNFR2), and diabetes. Waist circumference, leptin, and sTNFR2 were standardized. Cognitive impairment was defined as MMSE <21 or a z‐score < −1.5 standard deviation (SD). Incident cognitive impairment was defined among those without cognitive impairment at the index exam as follow‐up MMSE<21, z‐ score < −1.5, MMSE decline >1 point/year, or z‐score decline of >0.1 SD/year. Results: Among 1008 participants (70% women, mean age 62.9 years, 14.5% with obesity, 26% with diabetes), 132 (13%) had baseline cognitive impairment. Each SD higher waist circumference was associated with higher odds of cognitive impairment, odds ratio (OR) = 1.63; (95% confidence interval: 1.17, 2.24), with mediating pathways explaining 65% of the total effect (58% from diabetes; 7% from inflammation). At follow‐up (mean 6.8 years), 106 of 535 (19.8%) had developed cognitive impairment. Each SD higher waist circumference was associated with higher odds of developing cognitive impairment (OR = 1.87; 95%CI: 1.18, 2.74); the direct effect of waist circumference explained 37% of the total effect and mediating pathways explained 63% (61% from diabetes; 2% from inflammation), although individual pathways were not statistically supported in the smaller sample. Conclusion: Diabetes, and to a lesser degree, adiposity‐driven inflammation, appear to explain a substantial proportion of abdominal adiposity relationships with cognitive impairment. The impact of preventing and treating obesity on cognitive outcomes merits study. [ABSTRACT FROM AUTHOR]

Polygenic risk scores (PRS) are commonly used to quantify the inherited susceptibility for a trait, yet they fail to account for non-linear and interaction effects between single nucleotide polymorphisms (SNPs). We address this via a machine learning approach, validated in nine complex phenotypes in a multi-ancestry population. We use an ensemble method of SNP selection followed by gradient boosted trees (XGBoost) to allow for non-linearities and interaction effects. We compare our results to the standard, linear PRS model developed using PRSice, LDpred2, and lassosum2. Combining a PRS as a feature in an XGBoost model results in a relative increase in the percentage variance explained compared to the standard linear PRS model by 22% for height, 27% for HDL cholesterol, 43% for body mass index, 50% for sleep duration, 58% for systolic blood pressure, 64% for total cholesterol, 66% for triglycerides, 77% for LDL cholesterol, and 100% for diastolic blood pressure. Multi-ancestry trained models perform similarly to specific racial/ethnic group trained models and are consistently superior to the standard linear PRS models. This work demonstrates an effective method to account for non-linearities and interaction effects in genetics-based prediction models. Combining a standard polygenic risk score (PRS) as a feature in a machine learning model increases the percentage variance explained for those traits, helping to account for non-linearities or interaction effects in genetics-based prediction models. [ABSTRACT FROM AUTHOR]

Background: Cardiovascular health (CVH) from young adulthood is strongly associated with an individual's future risk of cardiovascular disease (CVD) and total mortality. Defining epigenomic biomarkers of lifelong CVH exposure and understanding their roles in CVD development may help develop preventive and therapeutic strategies for CVD.Methods: In 1085 CARDIA study (Coronary Artery Risk Development in Young Adults) participants, we defined a clinical cumulative CVH score that combines body mass index, blood pressure, total cholesterol, and fasting glucose measured longitudinally from young adulthood through middle age over 20 years (mean age, 25-45). Blood DNA methylation at >840 000 methylation markers was measured twice over 5 years (mean age, 40 and 45). Epigenome-wide association analyses on the cumulative CVH score were performed in CARDIA and compared in the FHS (Framingham Heart Study). We used penalized regression to build a methylation-based risk score to evaluate the risk of incident coronary artery calcification and clinical CVD events.Results: We identified 45 methylation markers associated with cumulative CVH at false discovery rate <0.01 (P=4.7E-7-5.8E-17) in CARDIA and replicated in FHS. These associations were more pronounced with methylation measured at an older age. CPT1A, ABCG1, and SREBF1 appeared as the most prominent genes. The 45 methylation markers were mostly located in transcriptionally active chromatin and involved lipid metabolism, insulin secretion, and cytokine production pathways. Three methylation markers located in genes SARS1, SOCS3, and LINC-PINT statistically mediated 20.4% of the total effect between CVH and risk of incident coronary artery calcification. The methylation risk score added information and significantly (P=0.004) improved the discrimination capacity of coronary artery calcification status versus CVH score alone and showed association with risk of incident coronary artery calcification 5 to 10 years later independent of cumulative CVH score (odds ratio, 1.87; P=9.66E-09). The methylation risk score was also associated with incident clinical CVD in FHS (hazard ratio, 1.28; P=1.22E-05).Conclusions: Cumulative CVH from young adulthood contributes to midlife epigenetic programming over time. Our findings demonstrate the role of epigenetic markers in response to CVH changes and highlight the potential of epigenomic markers for precision CVD prevention, and earlier detection of subclinical CVD, as well. [ABSTRACT FROM AUTHOR]

DNA methylation (DNAm) has been reported to be associated with many diseases and with mortality. We hypothesized that the integration of DNAm with clinical risk factors would improve mortality prediction. We performed an epigenome‐wide association study of whole blood DNAm in relation to mortality in 15 cohorts (n = 15,013). During a mean follow‐up of 10 years, there were 4314 deaths from all causes including 1235 cardiovascular disease (CVD) deaths and 868 cancer deaths. Ancestry‐stratified meta‐analysis of all‐cause mortality identified 163 CpGs in European ancestry (EA) and 17 in African ancestry (AA) participants at p < 1 × 10−7, of which 41 (EA) and 16 (AA) were also associated with CVD death, and 15 (EA) and 9 (AA) with cancer death. We built DNAm‐based prediction models for all‐cause mortality that predicted mortality risk after adjusting for clinical risk factors. The mortality prediction model trained by integrating DNAm with clinical risk factors showed an improvement in prediction of cancer death with 5% increase in the C‐index in a replication cohort, compared with the model including clinical risk factors alone. Mendelian randomization identified 15 putatively causal CpGs in relation to longevity, CVD, or cancer risk. For example, cg06885782 (in KCNQ4) was positively associated with risk for prostate cancer (Beta = 1.2, PMR = 4.1 × 10−4) and negatively associated with longevity (Beta = −1.9, PMR = 0.02). Pathway analysis revealed that genes associated with mortality‐related CpGs are enriched for immune‐ and cancer‐related pathways. We identified replicable DNAm signatures of mortality and demonstrated the potential utility of CpGs as informative biomarkers for prediction of mortality risk. [ABSTRACT FROM AUTHOR]

One mechanism by which genetic factors influence complex traits and diseases is altering gene expression. Direct measurement of gene expression in relevant tissues is rarely tenable; however, genetically regulated gene expression (GReX) can be estimated using prediction models derived from large multi-omic datasets. These approaches have led to the discovery of many gene-trait associations, but whether models derived from predominantly European ancestry (EA) reference panels can map novel associations in ancestrally diverse populations remains unclear. We applied PrediXcan to impute GReX in 51,520 ancestrally diverse Population Architecture using Genomics and Epidemiology (PAGE) participants (35% African American, 45% Hispanic/Latino, 10% Asian, and 7% Hawaiian) across 25 key cardiometabolic traits and relevant tissues to identify 102 novel associations. We then compared associations in PAGE to those in a random subset of 50,000 White British participants from UK Biobank (UKBB 50k) for height and body mass index (BMI). We identified 517 associations across 47 tissues in PAGE but not UKBB 50k , demonstrating the importance of diverse samples in identifying trait-associated GReX. We observed that variants used in PrediXcan models were either more or less differentiated across continental-level populations than matched-control variants depending on the specific population reflecting sampling bias. Additionally, variants from identified genes specific to either PAGE or UKBB 50k analyses were more ancestrally differentiated than those in genes detected in both analyses, underlining the value of population-specific discoveries. This suggests that while EA-derived transcriptome imputation models can identify new associations in non-EA populations, models derived from closely matched reference panels may yield further insights. Our findings call for more diversity in reference datasets of tissue-specific gene expression. [Display omitted] [ABSTRACT FROM AUTHOR]

Circulating total-tau levels can be used as an endophenotype to identify genetic risk factors for tauopathies and related neurological disorders. Here, we confirmed and better characterized the association of the 17q21 MAPT locus with circulating total-tau in 14,721 European participants and identified three novel loci in 953 African American participants (4q31, 5p13, and 6q25) at P < 5 × 10−8. We additionally detected 14 novel loci at P < 5 × 10−7, specific to either Europeans or African Americans. Using whole-exome sequence data in 2,279 European participants, we identified ten genes associated with circulating total-tau when aggregating rare variants. Our genetic study sheds light on genes reported to be associated with neurological diseases including stroke, Alzheimer's, and Parkinson's (F5, MAP1B, and BCAS3), with Alzheimer's pathological hallmarks (ADAMTS12, IL15, and FHIT), or with an important function in the brain (PARD3, ELFN2, UBASH3B, SLIT3, and NSD3), and suggests that the genetic architecture of circulating total-tau may differ according to ancestry. A meta-analysis of genome-wide association studies of circulating total-tau levels identifies loci specific to European or African American ancestries, providing further insight to the genetic etiology of neurological diseases. [ABSTRACT FROM AUTHOR]

Appetite regulatory neural network and adipocyte homeostasis molecular pathways are critical to long-term weight maintenance. Associations between obesity-related phenotypes and four genes in these pathways – leptin ( LEP), leptin receptor ( LEPR), neuropeptide Y2 receptor ( NPY2R) and peptide YY ( PYY) were examined in CARDIA Study participants (aged 18–30 at recruitment in 1985–6). Weight, BMI and waist circumference were measured at baseline and at years 2, 5, 7, 10, 15, and 20. Genotyping was conducted using tag SNPs characterising common genetic variations in these genes. Generalized estimating equation (GEE) models estimated associations between SNPs and repeated anthropometric measurements, controlling for sex and age. False discovery rate was used to adjust for multiple testing. In African-Americans, SNPs across the LEP gene demonstrated significant overall associations with all obesity-related phenotypes. The associations between LEP rs17151919 with weight tended to strengthen with time – the difference in weight associated with each additional minor allele increased from 2.6 kg at baseline to 4.8 kg at year 20 (SNP*time interaction p = 0.0193). NPY2R gene SNPs were associated with waist circumference among African-American men (p = 0.0462). In Caucasians, LEP SNPs also tended to be associated with weight (p = 0.0471), and PYY rs11684664 was associated with obesity-related phenotypes in women only (p = 0.010–0.026). Several LEP, and NPY2R and PYY SNPs were associated with obesity-related phenotypes in young adults, particularly among African-Americans. [ABSTRACT FROM AUTHOR]

Background: The most prominent risk factor for atrial fibrillation (AF) is chronological age; however, underlying mechanisms are unexplained. Algorithms using epigenetic modifications to the human genome effectively predict chronological age. Chronological and epigenetic predicted ages may diverge in a phenomenon referred to as epigenetic age acceleration (EAA), which may reflect accelerated biological aging. We sought to evaluate for associations between epigenetic age measures and incident AF.Methods: Measures for 4 epigenetic clocks (Horvath, Hannum, DNA methylation [DNAm] PhenoAge, and DNAm GrimAge) and an epigenetic predictor of PAI-1 (plasminogen activator inhibitor-1) levels (ie, DNAm PAI-1) were determined for study participants from 3 population-based cohort studies. Cox models evaluated for associations with incident AF and results were combined via random-effects meta-analyses. Two-sample summary-level Mendelian randomization analyses evaluated for associations between genetic instruments of the EAA measures and AF.Results: Among 5600 participants (mean age, 65.5 years; female, 60.1%; Black, 50.7%), there were 905 incident AF cases during a mean follow-up of 12.9 years. Unadjusted analyses revealed all 4 epigenetic clocks and the DNAm PAI-1 predictor were associated with statistically significant higher hazards of incident AF, though the magnitudes of their point estimates were smaller relative to the associations observed for chronological age. The pooled EAA estimates for each epigenetic measure, with the exception of Horvath EAA, were associated with incident AF in models adjusted for chronological age, race, sex, and smoking variables. After multivariable adjustment for additional known AF risk factors that could also potentially function as mediators, pooled EAA measures for 2 clocks remained statistically significant. Five-year increases in EAA measures for DNAm GrimAge and DNAm PhenoAge were associated with 19% (adjusted hazard ratio [HR], 1.19 [95% CI, 1.09-1.31]; P<0.01) and 15% (adjusted HR, 1.15 [95% CI, 1.05-1.25]; P<0.01) higher hazards of incident AF, respectively. Mendelian randomization analyses for the 5 EAA measures did not reveal statistically significant associations with AF.Conclusions: Our study identified adjusted associations between EAA measures and incident AF, suggesting that biological aging plays an important role independent of chronological age, though a potential underlying causal relationship remains unclear. These aging processes may be modifiable and not constrained by the immutable factor of time. [ABSTRACT FROM AUTHOR]

Background and purpose: The role of copy number variation (CNV) variation in stroke susceptibility and outcome has yet to be explored. The Copy Number Variation and Stroke (CaNVAS) Risk and Outcome study addresses this knowledge gap. Methods: Over 24,500 well-phenotyped IS cases, including IS subtypes, and over 43,500 controls have been identified, all with readily available genotyping on GWAS and exome arrays, with case measures of stroke outcome. To evaluate CNV-associated stroke risk and stroke outcome it is planned to: 1) perform Risk Discovery using several analytic approaches to identify CNVs that are associated with the risk of IS and its subtypes, across the age-, sex- and ethnicity-spectrums; 2) perform Risk Replication and Extension to determine whether the identified stroke-associated CNVs replicate in other ethnically diverse datasets and use biomarker data (e.g. methylation, proteomic, RNA, miRNA, etc.) to evaluate how the identified CNVs exert their effects on stroke risk, and lastly; 3) perform outcome-based Replication and Extension analyses of recent findings demonstrating an inverse relationship between CNV burden and stroke outcome at 3 months (mRS), and then determine the key CNV drivers responsible for these associations using existing biomarker data. Results: The results of an initial CNV evaluation of 50 samples from each participating dataset are presented demonstrating that the existing GWAS and exome chip data are excellent for the planned CNV analyses. Further, some samples will require additional considerations for analysis, however such samples can readily be identified, as demonstrated by a sample demonstrating clonal mosaicism. Conclusion: The CaNVAS study will cost-effectively leverage the numerous advantages of using existing case-control data sets, exploring the relationships between CNV and IS and its subtypes, and outcome at 3 months, in both men and women, in those of African and European-Caucasian descent, this, across the entire adult-age spectrum. [ABSTRACT FROM AUTHOR]

Background: Whether high blood pressure has a causal effect on cognitive function as early as middle age is unclear. We investigated whether high blood pressure (BP) causally impairs cognitive function at midlife using Mendelian Randomization (MR). Methods: We applied a two-sample MR approach to investigate the causal relationship between BP and midlife cognitive performance measured by the Digit Symbol Substitution Test (DSST), Rey Auditory Verbal Learning Test (RAVLT), and Stroop Interference test. We used a total of 109 genetic polymorphisms with established associations with BP as instrumental variables and estimated gene-cognitive function association in 1369 middle-aged adults (Mean age (SD): 50.8 (3.3), 54.0% women) from the CARDIA study. Results: A 10 mmHg increment in genetically-predicted systolic, diastolic, or pulse pressure was associated with a 4.9 to 7.7-point lower DSST score (P = 0.002, SBP; P = 0.005, DBP and P = 0.008, PP), while a 10 mmHg increment in genetically-predicted SBP was associated with a 0.7 point lower RAVLT and a 2.3 point higher Stroop (P = 0.046 and 0.011, respectively). Conclusions: This MR analysis shows that high BP, especially SBP, is causally associated with poorer processing speed, verbal memory, and executive function during midlife. These findings emphasize the need for further investigation of the role and mechanisms of BP dysregulation on cognitive health in middle age and perhaps, more broadly, across the lifespan. [ABSTRACT FROM AUTHOR]

Objective: Hispanics/Latinos are the largest ethnic/racial group in the U.S., have the highest prevalence of diabetes, and are at increased risk for neurodegenerative disorders. Currently, little is known about the relationship between diabetes and cognitive decline and disorders among diverse Hispanics/Latinos. The purpose of this study is to clarify these relationships in diverse middle-aged and older Hispanics/Latinos.Research Design and Methods: The Study of Latinos-Investigation of Neurocognitive Aging (SOL-INCA) is an ancillary study of the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). HCHS/SOL is a multisite (Bronx, NY; Chicago, IL; Miami, FL; and San Diego, CA), probability-sampled (i.e., representative of targeted populations), and prospective cohort study. Between 2016 and 2018, SOL-INCA enrolled diverse Hispanics/Latinos aged ≥50 years (n = 6,377). Global cognitive decline and mild cognitive impairment (MCI) were the primary outcomes.Results: Prevalent diabetes at visit 1, but not incident diabetes at visit 2, was associated with significantly steeper global cognitive decline (βGC = -0.16 [95% CI -0.25; -0.07]; P < 0.001), domain-specific cognitive decline, and higher odds of MCI (odds ratio 1.74 [95% CI 1.34; 2.26]; P < 0.001) compared with no diabetes in age- and sex-adjusted models.Conclusions: Diabetes was associated with cognitive decline and increased MCI prevalence among diverse Hispanics/Latinos, primarily among those with prevalent diabetes at visit 1. Our findings suggest that significant cognitive decline and MCI may be considered additional disease complications of diabetes among diverse middle-aged and older Hispanics/Latinos. [ABSTRACT FROM AUTHOR]

Background: Quantitative red blood cell (RBC) traits are highly polygenic clinically relevant traits, with approximately 500 reported GWAS loci. The majority of RBC trait GWAS have been performed in European- or East Asian-ancestry populations, despite evidence that rare or ancestry-specific variation contributes substantially to RBC trait heritability. Recently developed combined-phenotype methods which leverage genetic trait correlation to improve statistical power have not yet been applied to these traits. Here we leveraged correlation of seven quantitative RBC traits in performing a combined-phenotype analysis in a multi-ethnic study population. Results: We used the adaptive sum of powered scores (aSPU) test to assess combined-phenotype associations between ~ 21 million SNPs and seven RBC traits in a multi-ethnic population (maximum n = 67,885 participants; 24% African American, 30% Hispanic/Latino, and 43% European American; 76% female). Thirty-nine loci in our multi-ethnic population contained at least one significant association signal (p < 5E-9), with lead SNPs at nine loci significantly associated with three or more RBC traits. A majority of the lead SNPs were common (MAF > 5%) across all ancestral populations. Nineteen additional independent association signals were identified at seven known loci (HFE, KIT, HBS1L/MYB, CITED2/FILNC1, ABO, HBA1/2, and PLIN4/5). For example, the HBA1/2 locus contained 14 conditionally independent association signals, 11 of which were previously unreported and are specific to African and Amerindian ancestries. One variant in this region was common in all ancestries, but exhibited a narrower LD block in African Americans than European Americans or Hispanics/Latinos. GTEx eQTL analysis of all independent lead SNPs yielded 31 significant associations in relevant tissues, over half of which were not at the gene immediately proximal to the lead SNP. Conclusion: This work identified seven loci containing multiple independent association signals for RBC traits using a combined-phenotype approach, which may improve discovery in genetically correlated traits. Highly complex genetic architecture at the HBA1/2 locus was only revealed by the inclusion of African Americans and Hispanics/Latinos, underscoring the continued importance of expanding large GWAS to include ancestrally diverse populations. [ABSTRACT FROM AUTHOR]

Background: The American Heart Association, in conjunction with the National Institutes of Health, annually reports on the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).Methods: The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2020 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population, metrics to assess and monitor healthy diets, an enhanced focus on social determinants of health, a focus on the global burden of cardiovascular disease, and further evidence-based approaches to changing behaviors, implementation strategies, and implications of the American Heart Association's 2020 Impact Goals.Results: Each of the 26 chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.Conclusions: The Statistical Update represents a critical resource for the lay public, policy makers, media professionals, clinicians, healthcare administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions. [ABSTRACT FROM AUTHOR]

Methylation levels measured at defined sites across the genome have recently been shown to be correlated with an individual's chronological age. Age acceleration, or the difference between age estimated from DNA methylation status and chronological age, has been proposed as a novel biomarker of aging. In this study, the cross-sectional association between two different measures of age acceleration and cognitive function was investigated using whole blood samples from 2,157 African American participants 47-70 years of age in the population-based Atherosclerosis Risk in Communities (ARIC) Study. Cognition was evaluated using three domain-specific tests. A significant inverse association between a 1-year increase in age acceleration calculated using a blood-based age predictor and scores on the Word Fluency Test was found using a general linear model adjusted for chronological age, gender, and years of education (β = -0.140 words; p = .001) and after adding other potential confounding variables (β = -0.104 words, p = .023). The results were replicated in 1,670 European participants in the Generation Scotland: Scottish Family Health Study (fully adjusted model: β = -0.199 words; p = .034). A significant association was also identified in a trans-ethnic meta-analysis across cohorts that included an additional 708 European American ARIC study participants (fully adjusted model: β = -0.110 words, p = .003). There were no associations found using an estimate of age acceleration derived from multiple tissues. These findings provide evidence that age acceleration is a correlate of performance on a test of verbal fluency in middle-aged adults. [ABSTRACT FROM AUTHOR]

BACKGROUND: Inflammatory effects of ambient particulate matter (PM) air pollution exposures may underlie PM-related increases in cardiovascular disease risk and mortality, although evidence of PM-associated leukocytosis is inconsistent and largely based on small, cross-sectional, and/or unrepresentative study populations. OBJECTIVES: Our objective was to estimate PM-leukocyte associations among U.S.women and men in the Women's Health Initiative and Atherosclerosis Risk in Communities study (푛 = 165,675). METHODS: We based the PM-leukocyte estimations on up to four study visits per participant, at which peripheral blood leukocytes and geocoded address-specific concentrations of PM ≤10, ≤2.5, and 2.5-10μm in diameter (PM10, PM2.5, and PM2.5-10, respectively) were available. We multiply imputed missing data using chained equations and estimated PM-leukocyte count associations over daily to yearly PM exposure averaging periods using center-specific, linear, mixed, longitudinal models weighted for attrition and adjusted for sociodemographic, behavioral, meteorological, and geographic covariates. In a subset of participants with available data (푛 = 8,457), we also estimated PM-leukocyte proportion associations in compositional data analyses. RESULTS: We found a 12 cells/μL (95% confidence interval: -9, 33) higher leukocyte count, a 1.2% (0.6%, 1.8%) higher granulocyte proportion, and a -1.1% (-1.9%, -0.3%) lower CD8+ T-cell proportion per 10-μg/m³ increase in 1-month mean PM2.5. However, shorter-duration PM10 exposures were inversely and only modestly associated with leukocyte count. DISCUSSION: The PM2.5-leukocyte estimates, albeit imprecise, suggest that among racially, ethnically, and environmentally diverse U.S. populations, sustained, ambient exposure to fine PM may induce subclinical, but epidemiologically important, inflammatory effects. [ABSTRACT FROM AUTHOR]

The article highlights a report from the American Heart Association (AHA), in conjunction with the National Institutes of Health and other government agencies, on statistics related to heart disease, stroke, and the cardiovascular risk factors which include health behaviors and health factors that contribute to cardiovascular health. Topics include statistical update representing a critical resource for policy makers, clinicians, healthcare administrators, researchers, and health advocates.

Background and purpose: Polymorphisms in coagulation genes have been associated with early-onset ischemic stroke. Here we pursue an a priori hypothesis that genetic variation in the endothelial-based receptors of the thrombomodulin−protein C system (THBD and PROCR) may similarly be associated with early-onset ischemic stroke. We explored this hypothesis utilizing a multi-stage design of discovery and replication. Methods: Discovery was performed in the Genetics-of-Early-Onset Stroke (GEOS) Study, a biracial population-based case-control study of ischemic stroke among men and women aged 15–49 including 829 cases of first ischemic stroke (42.2% African-American) and 850 age-comparable stroke-free controls (38.1% African-American). Twenty-four single-nucleotide-polymorphisms (SNPs) in THBD and 22 SNPs in PROCR were evaluated. Following LD pruning (r2≥0.8), we advanced uncorrelated SNPs forward for association analyses. Associated SNPs were evaluated for replication in an early-onset ischemic stroke population (onset-age<60 years) consisting of 3676 cases and 21118 non-stroke controls from 6 case–control studies. Lastly, we determined if the replicated SNPs also associated with older-onset ischemic stroke in the METASTROKE data-base. Results: Among GEOS Caucasians, PROCR rs9574, which was in strong LD with 8 other SNPs, and one additional independent SNP rs2069951, were significantly associated with ischemic stroke (rs9574, OR = 1.33, p = 0.003; rs2069951, OR = 1.80, p = 0.006) using an additive-model adjusting for age, gender and population-structure. Adjusting for risk factors did not change the associations; however, associations were strengthened among those without risk factors. PROCR rs9574 also associated with early-onset ischemic stroke in the replication sample (OR = 1.08, p = 0.015), but not older-onset stroke. There were no PROCR associations in African-Americans, nor were there any THBD associations in either ethnicity. Conclusion: PROCR polymorphisms are associated with early-onset ischemic stroke in Caucasians. [ABSTRACT FROM AUTHOR]

We conducted an epigenome-wide association study on obesity-related traits. We used data from 2 prospective, population-based cohort studies: the Rotterdam Study (RS) (2006–2013) and the Atherosclerosis Risk in Communities (ARIC) Study (1990–1992). We used the RS (n = 1,450) as the discovery panel and the ARIC Study (n = 2,097) as the replication panel. Linear mixed-effect models were used to assess the cross-sectional associations between genome-wide DNA methylation in leukocytes and body mass index (BMI) and waist circumference (WC), adjusting for sex, age, smoking, leukocyte proportions, array number, and position on array. The latter 2 variables were modeled as random effects. Fourteen 5′-C-phosphate-G-3′ (CpG) sites were associated with BMI and 26 CpG sites with WC in the RS after Bonferroni correction (P < 1.07 × 10−7), of which 12 and 13 CpGs were replicated in the ARIC Study, respectively. The most significant novel CpGs were located on the Musashi RNA binding protein 2 gene (MSI2 ; cg21139312) and the leucyl-tRNA synthetase 2, mitochondrial gene (LARS2 ; cg18030453) and were associated with both BMI and WC. CpGs at BRDT , PSMD1 , IFI44L , MAP1A , and MAP3K5 were associated with BMI. CpGs at LGALS3BP , MAP2K3 , DHCR24 , CPSF4L , and TMEM49 were associated with WC. We report novel associations between methylation at MSI2 and LARS2 and obesity-related traits. These results provide further insight into mechanisms underlying obesity-related traits, which can enable identification of new biomarkers in obesity-related chronic diseases. [ABSTRACT FROM AUTHOR]

Background: Odd-numbered chain saturated fatty acids (OCSFA) have been associated with potential health benefits. Although some OCSFA (e.g., C15:0 and C17:0) are found in meats and dairy products, sources and metabolism of C19:0 and C23:0 are relatively unknown, and the influence of non-dietary determinants, including genetic factors, on circulating levels of OCSFA is not established. Objective: To elucidate the biological processes that influence circulating levels of OCSFA by investigating associations between genetic variation and OCSFA. Design: We performed a meta-analysis of genome-wide association studies (GWAS) of plasma phospholipid/erythrocyte levels of C15:0, C17:0, C19:0, and C23:0 among 11,494 individuals of European descent. We also investigated relationships between specific single nucleotide polymorphisms (SNPs) in the lactase (LCT) gene, associated with adult-onset lactase intolerance, with circulating levels of dairy-derived OCSFA, and evaluated associations of candidate sphingolipid genes with C23:0 levels. Results: We found no genome-wide significant evidence that common genetic variation is associated with circulating levels of C15:0 or C23:0. In two cohorts with available data, we identified one intronic SNP (rs13361131) in myosin X gene (MYO10) associated with C17:0 level (P = 1.37×10−8), and two intronic SNP (rs12874278 and rs17363566) in deleted in lymphocytic leukemia 1 (DLEU1) region associated with C19:0 level (P = 7.07×10−9). In contrast, when using a candidate-gene approach, we found evidence that three SNPs in LCT (rs11884924, rs16832067, and rs3816088) are associated with circulating C17:0 level (adjusted P = 4×10−2). In addition, nine SNPs in the ceramide synthase 4 (CERS4) region were associated with circulating C23:0 levels (adjusted P<5×10−2). Conclusions: Our findings suggest that circulating levels of OCSFA may be predominantly influenced by non-genetic factors. SNPs associated with C17:0 level in the LCT gene may reflect genetic influence in dairy consumption or in metabolism of dairy foods. SNPs associated with C23:0 may reflect a role of genetic factors in the synthesis of sphingomyelin. [ABSTRACT FROM AUTHOR]

Background: Adiposity depots may differentially affect cognition. African Americans (AA) have higher rates of obesity and dementia but lower visceral adipose tissue (VAT) than whites, yet are underrepresented in studies of adiposity and cognition. Our study compared relations of cognitive function to clinical adiposity measures and computed tomography (CT)-imaged abdominal adiposity in AA.Methods: CT-imaged subcutaneous adipose tissue (SAT) and VAT measurements were obtained in the AA cohort of the Genetic Epidemiology Network of Arteriopathy Study (N = 652, mean age 68 ± 8.4 years, 74% females, 59% obese, 82% hypertensive). Clinical adiposity measures included waist circumference (WC) and body mass index (BMI). Global cognition was operationalized as a global cognitive z-score generated from the average of four cognitive domain z-scores. Generalized estimating equations were used to examine cross-sectional associations between individual standardized adiposity measures and cognition, accounting for age, sex, education, smoking status, and familial clustering. A collective model was constructed including multiple supported adiposity measures and age-by-adiposity interactions.Results: In the collective model, higher WC was associated with worse global cognition, β = -0.12 (95%CI: -0.21, -0.03); higher SAT was associated with better cognition, β = 0.09 (0.01, 0.18); higher BMI was associated with worse cognition at younger ages with attenuation at older ages (BMI-by-age-interaction p = .004). VAT was not significantly associated with global cognition, β = -0.03 (-0.07, 0.02).Conclusions: WC may be the simplest and most efficient measure of adiposity to assess with respect to cognition in clinical settings, although studies to determine mechanistic effects of subcutaneous and other adiposity depots on cognition are warranted. [ABSTRACT FROM AUTHOR]

Background: Clinical and epidemiological studies of older persons have implicated clusterin in Alzheimer's disease (AD) pathogenesis. In the context of identifying early biomarkers of risk, we examined associations of plasma clusterin and characteristics of AD in middle-aged individuals from the community. Materials and methods: Subjects were 639 cognitively normal individuals (mean age 50 ± 3.5) from the Coronary Artery Risk Development in Young Adults (CARDIA) Brain MRI sub-study. Clusterin was quantified using ELISA (mean 255± 31 ng/ml). Associations were assessed between clusterin and volumes of brain regions known to atrophy in early AD, including entorhinal cortex (ECV), hippocampus (HV), and medial temporal lobe (MTLV) volumes (cm3). Total brain volume (TBV) and volumes of structures affected in later AD were examined for comparison. Results: In multivariable models, higher clusterin had a negative non-linear association with ECV (combined left and right hemispheres), and this association was influenced by the highest clusterin levels. Compared to mean clusterin, 1 and 2 standard deviation (SD) level increases in clusterin were associated with -2.1% (95% CI: -3.3,-0.9) and -7.3% (95% CI: -11.3,-3.3) lower ECV, respectively. Similar relationships were observed between clusterin and HV, although the relationship was stronger for left-side HV than the right-side. However, the association was not significant after adjusting for covariates. Negative non-linear associations between clusterin and MTLV were strongest for the left side: compared to mean clusterin, 1 and 2 SD level increases in clusterin were associated with -0.9% (95% CI: -1.9, 0.1) and -3.7% (95% CI: -7.1, -0.3) lower MTLV. There were no significant associations between clusterin and brain structures affected in later AD. Conclusions: In middle-aged adults unselected for AD, plasma clusterin was associated with lower volume of the entorhinal cortex, an area that atrophies early in AD. Clusterin could be informative as part of a multi-component preclinical marker for AD. [ABSTRACT FROM AUTHOR]

Objective: We performed single-variant and gene-based association analyses of plasma amyloid-β (aβ) concentrations using whole exome sequence from 1,414 African and European Americans. Our goal was to identify genes that influence plasma aβ42 concentrations and aβ42:aβ40 ratios in late middle age (mean = 59 years), old age (mean = 77 years), or change over time (mean = 18 years). Methods: Plasma aβ measures were linearly regressed onto age, gender, APOE ε4 carrier status, and time elapsed between visits (fold-changes only) separately by race. Following inverse normal transformation of the residuals, seqMeta was used to conduct race-specific single-variant and gene-based association tests while adjusting for population structure. Linear regression models were fit on autosomal variants with minor allele frequencies (MAF)≥1%. T5 burden and Sequence Kernel Association (SKAT) gene-based tests assessed functional variants with MAF≤5%. Cross-race fixed effects meta-analyses were Bonferroni-corrected for the number of variants or genes tested. Results: Seven genes were associated with aβ in late middle age or change over time; no associations were identified in old age. Single variants in KLKB1 (rs3733402; p = 4.33x10-10) and F12 (rs1801020; p = 3.89x10-8) were significantly associated with midlife aβ42 levels through cross-race meta-analysis; the KLKB1 variant replicated internally using 1,014 additional participants with exome chip. ITPRIP, PLIN2, and TSPAN18 were associated with the midlife aβ42:aβ40 ratio via the T5 test; TSPAN18 was significant via the cross-race meta-analysis, whereas ITPRIP and PLIN2 were European American-specific. NCOA1 and NT5C3B were associated with the midlife aβ42:aβ40 ratio and the fold-change in aβ42, respectively, via SKAT in African Americans. No associations replicated externally (N = 725). Conclusion: We discovered age-dependent genetic effects, established associations between vascular-related genes (KLKB1, F12, PLIN2) and midlife plasma aβ levels, and identified a plausible Alzheimer’s Disease candidate gene (ITPRIP) influencing cell death. Plasma aβ concentrations may have dynamic biological determinants across the lifespan; plasma aβ study designs or analyses must consider age. [ABSTRACT FROM AUTHOR]

Background: Pathways directing endogenous stem/progenitor cells to restore normal architecture and function of damaged/diseased lungs remain underexplored. Published data have revealed that alveolar progenitor type II cell (ATIIC)-derived signaling promotes re-epithelialization of injured alveoli, yet the underlying mechanism is unknown. Here we aim to define the role of ATIIC-derived exosome miRNA signaling in controlling ATIIC-specific proliferation or differentiation in response to injury. Methods: Pluripotent stem cell-derived cultures, which contain early lung stem/progenitor populations that can subsequently differentiate into ATIICs, were used as a model for unbiased screening and identification of ATIIC phenotype-specific exosome miRNA signaling, and human induced pluripotent stem cell-derived ATIICs (hiPSC-ATIICs) were employed to examine the molecular basis of key exosome miRNA signaling in promoting ATIIC-specific proliferation. QRT-PCR was performed to examine expression pattern of ATIIC-derived key exosome miRNA in an alveolar injury model and in injured human lungs. Results: We show that human ATIIC line (A549)-derived exosome miR-371b-5p promotes ATIIC-specific proliferation, but not differentiation, in differentiating cultures of pluripotent stem cells. Using 3'UTR-driven luciferase reporters, we identified PTEN as a direct target of miR-371b-5p. Transfection of miR-371b-5p mimic into hiPSC-ATIICs leads to significantly decreased expression of endogenous PTEN, which stimulates phosphorylation of Akt and its downstream substrates, GSK3β and FOXOs, promoting cell proliferation. While not expressed in normal ATIIC phenotypes, the exosome miR-371b-5p expression is significantly induced after hiPSC-ATIICs or hATIICs (human primary ATIICs) are subjected to bleomycin-induced injury. To rule out that the ATIIC-derived exosome-miRNAs are merely a cell culture phenomenon, we transplanted hiPSC-ATIICs into bleomycin-challenged lungs of mice, and found that the transplanted hiPSC-ATIICs engraft and express exosome miR-371b-5p, along with additional survival of numerous mouse ATIICs in bleomycin-injured lungs. Consistent with these findings, significant levels of exosome miR-371b-5p were also detected in lavage samples of patients with acute pneumonia, but not in those from patients without pulmonary disorders. Conclusions: Collectively, our data strongly suggest that ATIIC-derived exosome miR-371b-5p may serve as a niche signaling to augment ATIIC survival/proliferation, promoting re-epithelialization of injured alveoli and thus provide a promising novel target to develop treatment for currently incurable lung diseases [ABSTRACT FROM AUTHOR]

Most body mass index (BMI) genetic loci have been identified in studies of primarily European ancestries. The effect of these loci in other racial/ethnic groups is less clear. Thus, we aimed to characterize the generalizability of 170 established BMI variants, or their proxies, to diverse US populations and trans-ethnically fine-map 36 BMI loci using a sample of >102,000 adults of African, Hispanic/Latino, Asian, European and American Indian/Alaskan Native descent from the Population Architecture using Genomics and Epidemiology Study. We performed linear regression of the natural log of BMI (18.5-70 kg/m) on the additive single nucleotide polymorphisms (SNPs) at BMI loci on the MetaboChip (Illumina, Inc.), adjusting for age, sex, population stratification, study site, or relatedness. We then performed fixed-effect meta-analyses and a Bayesian trans-ethnic meta-analysis to empirically cluster by allele frequency differences. Finally, we approximated conditional and joint associations to test for the presence of secondary signals. We noted directional consistency with the previously reported risk alleles beyond what would have been expected by chance (binomial p < 0.05). Nearly, a quarter of the previously described BMI index SNPs and 29 of 36 densely-genotyped BMI loci on the MetaboChip replicated/generalized in trans-ethnic analyses. We observed multiple signals at nine loci, including the description of seven loci with novel multiple signals. This study supports the generalization of most common genetic loci to diverse ancestral populations and emphasizes the importance of dense multiethnic genomic data in refining the functional variation at genetic loci of interest and describing several loci with multiple underlying genetic variants. [ABSTRACT FROM AUTHOR]