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C-Reactive protein (CRP) and monocyte chemoattractant protein-1 (MCP-1) are both implicated in the peripheral proinflammatory cascade and blood-brain barrier (BBB) disruption. Since the blood CRP level increases Alzheimer's disease (AD) risk depending on the apolipoprotein E (APOE) genotype, we hypothesized that the blood MCP-1 level exerts different effects on the AD risk depending on the genotypes.Using multiple regression analyses, data from the Framingham Heart Study (n = 2884) and Alzheimer's Disease Neuroimaging Initiative study (n = 231) were analyzed.An elevated blood MCP-1 level was associated with AD risk in major histocompatibility complex, Class II, DR beta 1 (HLA-DRB1) rs9271192-AC/CC (hazard ratio [HR] = 3.07, 95% confidence interval [CI] = 1.50-6.28, p = 0.002) and in APOE ε4 carriers (HR = 3.22, 95% CI = 1.59-6.53, p = 0.001). In contrast, among HLA-DRB1 rs9271192-AA and APOE ε4 noncarriers, blood MCP-1 levels were not associated with these phenotypes.Since HLA-DRB1 and APOE are expressed in the BBB, blood MCP-1 released in the peripheral inflammatory cascade may function as a mediator of the effects of HLA-DRB1 rs9271192-AC/CC and APOE ε4 genotypes on AD pathogenesis in the brain via the BBB pathways.

We recently derived an absolute breast cancer risk prediction model, the Black Women’s Health Study (BWHS) model, for breast cancer in U.S. Black women using data from three large case-control studies and validated it in independent prospective data from the Black Women’s Health Study (Palmer 2021). The BWHS model includes epidemiologic risk factors as well as family history of breast cancer and family history of prostate cancer. It does not include genetic variants because at the time of model development breast cancer polygenic risk scores performed poorly in women of predominantly African ancestry, primarily due to differences in allele frequency and linkage disequilibrium. More recently, Gao et al. (2022) developed and tested a polygenic risk score (PRS) using 56,943 SNPs for breast cancer in women of African ancestry (AA) based on 9,235 breast cancer cases and 10,184 controls from a large pooled analysis of studies from African American and African women; the c-statistic from cross-validation was 0.581, considerably better than in previous efforts. We evaluated whether adding this AA-PRS to the BWHS risk prediction model would improve risk stratification. We conducted a nested case-control study of 901 breast cancer cases and 1,576 controls matched on age and most recent questionnaire completed from among BWHS participants for whom genome-wide association data were available and who had not been included in the collaboration from which the PRS was derived and tested. We examined discriminatory accuracy, estimated by the area under the receiver operating characteristic curve (AUC), for the risk prediction model alone, the PRS alone, and the combination of risk prediction model and PRS, controlling for the matching factor “questionnaire cycle”. We conducted the analyses within strata of 5-year age and then combined results using inverse-variance weighting. In preliminary analyses, the AUC was 0.579 for the risk prediction model alone and 0.600 for the AA-PRS alone. When the AA-PRS and the BWHS risk prediction model were both used as predictors in a logistic regression model, the AUC increased from 0.579 to 0.622. This improvement in risk stratification is similar to what Kachuri et al. (2020) obtained in an analysis of U.K. Biobank data, where adding a PRS to epidemiologic and personal risk factors showed an improvement from 0.572 to 0.635 in women of European ancestry. The present study provides external validation of a recently derived AA PRS and demonstrates the potential for improving risk stratification for U.S. Black women by adding a PRS to a breast cancer risk prediction model that already includes family history of breast cancer. Citation Format: Gary R. Zirpoli, Kathryn L. Lunetta, Ruth M. Pfeiffer, Julie R. Palmer. PD14-06 Polygenic risk score added to risk calculator improves prediction of breast cancer in U.S. Black women [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr PD14-06.

Background: Rare sequence variation in genes underlying cardiac repolarization and common polygenic variation influence QT interval duration. However, current clinical genetic testing of individuals with unexplained QT prolongation is restricted to examination of monogenic rare variants. The recent emergence of large-scale biorepositories with sequence data enables examination of the joint contribution of rare and common variations to the QT interval in the population. Methods: We performed a genome-wide association study of the QTc in 84 630 UK Biobank participants and created a polygenic risk score (PRS). Among 26 976 participants with whole-genome sequencing and ECG data in the TOPMed (Trans-Omics for Precision Medicine) program, we identified 160 carriers of putative pathogenic rare variants in 10 genes known to be associated with the QT interval. We examined QTc associations with the PRS and with rare variants in TOPMed. Results: Fifty-four independent loci were identified by genome-wide association study in the UK Biobank. Twenty-one loci were novel, of which 12 were replicated in TOPMed. The PRS composed of 1 110 494 common variants was significantly associated with the QTc in TOPMed (ΔQTc /decile of PRS =1.4 ms [95% CI, 1.3 to 1.5]; P =1.1×10 -196 ). Carriers of putative pathogenic rare variants had longer QTc than noncarriers (ΔQTc=10.9 ms [95% CI, 7.4 to 14.4]). Of individuals with QTc>480 ms, 23.7% carried either a monogenic rare variant or had a PRS in the top decile (3.4% monogenic, 21% top decile of PRS). Conclusions: QTc duration in the population is influenced by both rare variants in genes underlying cardiac repolarization and polygenic risk, with a sizeable contribution from polygenic risk. Comprehensive assessment of the genetic determinants of QTc prolongation includes incorporation of both polygenic and monogenic risk.

Background: Genetic variants in LMNA may cause cardiac disease, but population-level contributions of variants to cardiac disease burden are not well-characterized. Objectives: We sought to determine the frequency and contribution of rare LMNA variants to cardiomyopathy and arrhythmia risk among ambulatory adults. Methods: We included 185,990 UK Biobank participants with whole-exome sequencing. We annotated rare loss-of-function and missense LMNA variants for functional effect using 30 in silico prediction tools. We assigned a predicted functional effect weight to each variant and calculated a score for each carrier. We tested associations between the LMNA score and arrhythmia (atrial fibrillation, bradyarrhythmia, ventricular arrhythmia) or cardiomyopathy outcomes (dilated cardiomyopathy and heart failure). We also examined associations for variants located upstream vs downstream of the nuclear localization signal. Results: Overall, 1,167 (0.63%) participants carried an LMNA variant and 15,079 (8.11%) had an arrhythmia or cardiomyopathy event during a median follow-up of 10.9 years. The LMNA score was associated with arrhythmia or cardiomyopathy (OR: 2.21; P < 0.001) and the association was more significant when restricted to variants upstream of the nuclear localization signal (OR: 5.05; P < 0.001). The incidence rate of arrhythmia or cardiomyopathy was 8.43 per 1,000 person-years (95% CI: 6.73-10.12 per 1,000 person-years) among LMNA variant carriers and 6.38 per 1,000 person-years (95% CI: 6.27-6.50 per 1,000 person-years) among noncarriers. Only 3 (1.2%) of the variants were reported as pathogenic in ClinVar. Conclusions: Middle-aged adult carriers of rare missense or loss-of-function LMNA variants are at increased risk for arrhythmia and cardiomyopathy.

With the emergence of large-scale sequencing data, methods for improving power in rare variant association tests are needed. Here we show that adjusting for common variant polygenic scores improves yield in gene-based rare variant association tests across 65 quantitative traits in the UK Biobank (up to 20% increase at α = 2.6 × 10−6), without marked increases in false-positive rates or genomic inflation. Benefits were seen for various models, with the largest improvements seen for efficient sparse mixed-effects models. Our results illustrate how polygenic score adjustment can efficiently improve power in rare variant association discovery.

Supplementary Table S1. Associations of Overall Breast Cancer Risk with 74 Breast Cancer Risk Variants in African Americans with Study-specific Results.

Supplementary Figure S1, Supplementary Figure S1. Regional plots of 3p24, 11q13, 12p11, 14q13, 16q12/TOX3, 16q12/FTO, 16q23, and 19p13.

List of Disease and Phenotype Associations used to Generate list of GWAS genes used to prioritize immune pathways

Supplementary Table S4. Associations with 74 Breast Cancer Risk Variants in African Americans by Estrogen Receptor (ER) Status.

Description of Study Populations in AMBER Consortium

Supplementary Table S2. Information about the 70 regions fine-mapped.

Supplementary Fig Leg

Immune-related genes found to be associated with breast cancer in AMBER

Supplementary Figure S2. Supplementary Figure S2. Genome browser views of 3p24, 11q13, 12p11, 14q13, 16q12/TOX3, 16q12/FTO,16q23, and 19p13.

Supplemental Table 1. Covariate characteristics of cases controls in the AMBER Consortium stratified by study; Supplemental Table 2. Recent alcohol intake (drinks per week) in relation to invasive breast cancer stratified by smoking status in the AMBER Consortium; Supplemental Table 3. Recent alcohol intake (drinks per week) in relation to invasive breast cancer stratified by lifetime duration of oral contraceptive use in the AMBER consortium; Supplemental Table 4. Recent alcohol intake (drinks per week) in relation to invasive breast cancer stratified by menopausal status in the AMBER consortium; Supplemental Figure 1. Flexible modeling of drinks per week as a squared term versus the log odds (95% confidence interval) of breast cancer in the AMBER consortium

Supplementary Table S5, a. Associations with better markers in African Americans. b. Associations with Secondary Signals in African Americans.

Background: Genome-wide association studies have identified approximately 100 common genetic variants associated with breast cancer risk, the majority of which were discovered in women of European ancestry. Because of different patterns of linkage disequilibrium, many of these genetic markers may not represent signals in populations of African ancestry.Methods: We tested 74 breast cancer risk variants and conducted fine-mapping of these susceptibility regions in 6,522 breast cancer cases and 7,643 controls of African ancestry from three genetic consortia (AABC, AMBER, and ROOT).Results: Fifty-four of the 74 variants (73%) were found to have ORs that were directionally consistent with those previously reported, of which 12 were nominally statistically significant (P < 0.05). Through fine-mapping, in six regions (3p24, 12p11, 14q13, 16q12/FTO, 16q23, 19p13), we observed seven markers that better represent the underlying risk variant for overall breast cancer or breast cancer subtypes, whereas in another two regions (11q13, 16q12/TOX3), we identified suggestive evidence of signals that are independent of the reported index variant. Overlapping chromatin features and regulatory elements suggest that many of the risk alleles lie in regions with biological functionality.Conclusions: Through fine-mapping of known susceptibility regions, we have revealed alleles that better characterize breast cancer risk in women of African ancestry.Impact: The risk alleles identified represent genetic markers for modeling and stratifying breast cancer risk in women of African ancestry. Cancer Epidemiol Biomarkers Prev; 26(7); 1016–26. ©2017 AACR.

Supplementary Table S6, a. Conditional Analysis on 14q13 and 16q12. b. Haplotype Analysis of associations with ER+ breast cancer on putative signals on 16q12.

Background: Constitutional immunity shaped by exposure to endemic infectious diseases and parasitic worms in Sub-Saharan Africa may play a role in the etiology of breast cancer among African American (AA) women.Methods: A total of 149,514 gene variants in 433 genes across 45 immune pathways were analyzed in the AMBER consortium among 3,663 breast cancer cases and 4,687 controls. Gene-based pathway analyses were conducted using the adaptive rank truncated product statistic for overall breast cancer risk, and risk by estrogen receptor (ER) status. Unconditional logistic regression analysis was used to estimate ORs and 95% confidence intervals (CIs) for single variants.Results: The top pathways were Interleukin binding (P = 0.01), Biocarta TNFR2 (P = 0.005), and positive regulation of cytokine production (P = 0.024) for overall, ER+, and ER− cancers, respectively. The most significant gene was IL2RB (P = 0.001) for overall cancer, with rs228952 being the top variant identified (OR = 0.85; 95% CI, 0.79–0.92). Only BCL3 contained a significant variant for ER+ breast cancer. Variants in IL2RB, TLR6, IL8, PRKDC, and MAP3K1 were associated with ER− disease. The only genes showing heterogeneity between ER− and ER+ cancers were TRAF1, MAP3K1, and MAPK3 (P ≤ 0.02). We also noted genes associated with autoimmune and atopic disorders.Conclusions: Findings from this study suggest that genetic variants in immune pathways are relevant to breast cancer susceptibility among AA women, both for ER+ and ER− breast cancers.Impact: Results from this study extend our understanding of how inherited genetic variation in immune pathways is relevant to breast cancer susceptibility. Cancer Epidemiol Biomarkers Prev; 27(3); 321–30. ©2018 AACR.

SummaryCerebrovascular damage coexists with Alzheimer’s disease (AD) pathology and increases AD risk. However, it is unclear whether endothelial progenitor cells reduce AD risk via cerebrovascular repair. By using the Framingham Heart Study (FHS) offspring cohort, which includes data on different progenitor cells, the incidence of AD dementia, peripheral and cerebrovascular pathologies, and genetic data (n = 1,566), we found that elevated numbers of circulating endothelial progenitor cells with CD34+CD133+ co-expressions had a dose-dependent association with decreased AD risk (HR = 0.67, 95% CI: 0.46-0.96, p = 0.03) after adjusting for age, sex, years of education, andAPOEε4. With stratification, this relationship was only significant among those individuals who had vascular pathologies, especially hypertension (HTN) and cerebral microbleeds (CMB), but not among those individuals who had neither peripheral nor central vascular pathologies. We applied a genome-wide association study (GWAS) and found that the number of CD34+CD133+ cells impacted AD risk depending on the homozygous genotypes of two genes:KIRREL3rs580382 CC carriers (HR = 0.31, 95% CI: 0.17-0.57, pKIRREL3rs4144611 TT carriers (HR = 0.29, 95% CI: 0.15-0.57, pEXOC6Brs61619102 CC carriers (HR = 0.49, 95% CI: 0.31-0.75, pKIRREL3TT/CT or GG/GT carriers andEXOC6BGG/GC carriers. Our findings suggest that circulating CD34+CD133+ endothelial progenitor cells can be therapeutic in reducing AD risk in the presence of cerebrovascular pathology, especially inKIRREL3andEXOC6Bgenotype carriers.

Apolipoprotein ε4 (APOE ε4) is the most significant genetic risk factor for late-onset Alzheimer’s disease (AD). Elevated blood C-reactive protein (CRP) further increases the risk of AD for people carrying the APOE ε4 allele. We hypothesized that CRP, as a key inflammatory element, could modulate the impact of other genetic variants on AD risk. We selected ten single nucleotide polymorphisms (SNPs) in reported AD risk loci encoding proteins related to inflammation. We then tested the interaction effects between these SNPs and blood CRP levels on AD incidence using the Cox proportional hazards model in UK Biobank (n = 279,176 white participants with 803 incident AD cases). The five top SNPs were tested for their interaction with different CRP cutoffs for AD incidence in the Framingham Heart Study (FHS) Generation 2 cohort (n = 3009, incident AD = 156). We found that for higher concentrations of serum CRP, the AD risk increased for SNP genotypes in 3 AD-associated genes (SPI1, CD33, and CLU). Using the Cox model in stratified genotype analysis, the hazard ratios (HRs) for the association between a higher CRP level (≥10 vs. p SPI1 rs1057233-AA genotype, 1.75 (95% CI: 1.20–2.55, p = 0.004) for the CD33 rs3865444-CC genotype, and 1.76 (95% CI: 1.25–2.48, p = 0.001) for the CLU rs9331896-C genotype. In contrast, these associations were not observed in the other genotypes of these genes. Finally, two SNPs were validated in 321 Alzheimer’s Disease Neuroimaging (ADNI) Mild Cognitive Impairment (MCI) patients. We observed that the SPI1 and CD33 genotype effects were enhanced by elevated CRP levels for the risk of MCI to AD conversion. Furthermore, the SPI1 genotype was associated with CSF AD biomarkers, including t-Tau and p-Tau, in the ADNI cohort when the blood CRP level was increased (p SPI1 and CD33 in addition to APOE ε4 on AD risk. Monitoring peripheral CRP levels may be helpful for precise intervention and prevention of AD for these genotype carriers.

Because regulation of gene expression is heritable and context-dependent, we investigated AD-related gene expression patterns in cell types in blood and brain. Cis-expression quantitative trait locus (eQTL) mapping was performed genome-wide in blood from 5257 Framingham Heart Study (FHS) participants and in brain donated by 475 Religious Orders Study/Memory & Aging Project (ROSMAP) participants. The association of gene expression with genotypes for all cis SNPs within 1 Mb of genes was evaluated using linear regression models for unrelated subjects and linear-mixed models for related subjects. Cell-type-specific eQTL (ct-eQTL) models included an interaction term for the expression of “proxy” genes that discriminate particular cell type. Ct-eQTL analysis identified 11,649 and 2533 additional significant gene-SNP eQTL pairs in brain and blood, respectively, that were not detected in generic eQTL analysis. Of note, 386 unique target eGenes of significant eQTLs shared between blood and brain were enriched in apoptosis and Wnt signaling pathways. Five of these shared genes are established AD loci. The potential importance and relevance to AD of significant results in myeloid cell types is supported by the observation that a large portion of GWS ct-eQTLs map within 1 Mb of established AD loci and 58% (23/40) of the most significant eGenes in these eQTLs have previously been implicated in AD. This study identified cell-type-specific expression patterns for established and potentially novel AD genes, found additional evidence for the role of myeloid cells in AD risk, and discovered potential novel blood and brain AD biomarkers that highlight the importance of cell-type-specific analysis.

The Trans-Omics for Precision Medicine (TOPMed) programme seeks to elucidate the genetic architecture and biology of heart, lung, blood and sleep disorders, with the ultimate goal of improving diagnosis, treatment and prevention of these diseases. The initial phases of the programme focused on whole-genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here we describe the TOPMed goals and design as well as the available resources and early insights obtained from the sequence data. The resources include a variant browser, a genotype imputation server, and genomic and phenotypic data that are available through dbGaP (Database of Genotypes and Phenotypes)1. In the first 53,831 TOPMed samples, we detected more than 400 million single-nucleotide and insertion or deletion variants after alignment with the reference genome. Additional previously undescribed variants were detected through assembly of unmapped reads and customized analysis in highly variable loci. Among the more than 400 million detected variants, 97% have frequencies of less than 1% and 46% are singletons that are present in only one individual (53% among unrelated individuals). These rare variants provide insights into mutational processes and recent human evolutionary history. The extensive catalogue of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and noncoding sequence variants to phenotypic variation. Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and reach of genome-wide association studies to include variants down to a frequency of approximately 0.01%., The goals, resources and design of the NHLBI Trans-Omics for Precision Medicine (TOPMed) programme are described, and analyses of rare variants detected in the first 53,831 samples provide insights into mutational processes and recent human evolutionary history.

Alzheimer's disease (AD) is a pervasive neurodegeneration disease with high heritability. In this study, we employed CRISPR-Cas9-engineered technology to investigate the effects of a rare mutation (rs144662445) in the A kinase anchoring protein 9 (AKAP9) gene, which is associated with AD in African Americans (AA), on tau pathology and the tau interactome in SH-SY5Y P301L neuron-like cells. The mutation significantly increased the level of phosphorylated tau, specifically at the site Ser396/Ser404. Moreover, analyses of the tau interactome measured by affinity purification-mass spectrometry revealed that differentially expressed tau-interacting proteins in AKAP9 mutant cells were associated with RNA translation, RNA localization and oxidative activity, recapitulating the tau interactome signature previously reported with human AD brain samples. Importantly, these results were further validated by functional studies showing a significant reduction in protein synthesis activity and excessive oxidative stress in AKAP9 mutant compared with wild type cells in a tau-dependent manner, which are mirrored with pathological phenotype frequently seen in AD. Our results demonstrated specific effects of rs14462445 on mis-processing of tau and suggest a potential role of AKAP9 in AD pathogenesis.

Variants in the tau gene (MAPT) region are associated with breast cancer in women and Alzheimer's disease (AD) among persons lacking apolipoprotein E ε4 (ε4-).To identify novel genes associated with tau-related pathology, we conducted two genome-wide association studies (GWAS) for AD, one among 10,340 ε4- women in the Alzheimer's Disease Genetics Consortium (ADGC) and another in 31 members (22 women) of a consanguineous Hutterite kindred.We identified novel associations of AD with MGMT variants in the ADGC (rs12775171, odds ratio [OR] = 1.4, P = 4.9 × 10These findings suggest that epigenetically regulated MGMT expression is involved in AD pathogenesis, especially in women.

Backgrounds and aims: Several genes are known to contribute to the levels and metabolism of HDL-C, however, their protective effects in cardiovascular disease (CVD), healthy aging, and longevity are complex and poorly understood. It is also unclear if these genes predict longitudinal HDL-C change. We aimed to identify loci influencing HDL-C change. Methods: We performed a genome-wide association study (GWAS) with harmonized HDL-C and imputed genotype in three family-based studies recruited for exceptional survival (Long Life Family Study), from community-based (Framingham Heart Study) and enriched for CVD (Family Heart Study). In 7738 individuals with at least 2 visits, we employed a growth curve model to estimate the random linear trajectory parameter of age-sex-adjusted HDL-C for each person. GWAS was performed using a linear regression model on HDL-C change accounting for kinship correlations, population structure, and differences among studies. Results: We identified a novel association for HDL-C with GRID1 (p = 5.43 × 10−10), which encodes a glutamate receptor channel subunit involved in synaptic plasticity. Seven suggestive novel loci (p < 1.0 × 10−6; MBOAT2, LINC01876-NR4A2, NTNG2, CYSLTR2, SYNE2, CTXND1-LINC01314, and CYYR1) and a known lipid gene (ABCA10) showed associations with HDL-C change. Two additional sex-specific suggestive loci were identified in women (DCLK2 and KCNJ2). Several of these genetic variants are associated with lipid-related conditions influencing cardiovascular and metabolic health, have predictive regulatory function, and are involved in lipid-related pathways. Conclusions: Modeling longitudinal HDL-C in prospective studies, with differences in healthy aging, longevity and CVD risk, contributed to gene discovery and provided insights into mechanisms of HDL-C regulation.

Aim: Racial disparities in opioid use disorder (OUD) management exist, however, and there is limited research on factors that influence opioid cessation in different population groups. Methods: We employed multiple machine learning prediction algorithms least absolute shrinkage and selection operator, random forest, deep neural network, and support vector machine) to assess factors associated with ceasing opioid use in a sample of 1,192 African Americans (AAs) and 2,557 individuals of European ancestry (EAs) who met Diagnostic and Statistical Manual of Mental Disorders, 5th Edition criteria for OUD. Values for nearly 4,000 variables reflecting demographics, alcohol and other drug use, general health, non-drug use behaviors, and diagnoses for other psychiatric disorders, were obtained for each participant from the Semi-Structured Assessment for Drug Dependence and Alcoholism, a detailed semi-structured interview. Results: Support vector machine models performed marginally better on average than other machine learning methods with maximum prediction accuracies of 75.4% in AAs and 79.4% in EAs. Subsequent stepwise regression considered the 83 most highly ranked variables across all methods and models and identified less recent cocaine use (AAs: odds ratio (OR) = 1.82 , P = 9.19 × 10-5; EAs: OR = 1.91, P = 3.30 × 10-15), shorter duration of opioid use (AAs: OR = 0.55, P = 5.78 × 10-6; EAs: OR = 0.69, P = 3.01 × 10-7), and older age (AAs: OR = 2.44, P = 1.41 × 10-12; EAs: OR = 2.00, P = 5.74 × 10-9) as the strongest independent predictors of opioid cessation in both AAs and EAs. Attending self-help groups for OUD was also an independent predictor (P < 0.05) in both population groups, while less gambling severity (OR = 0.80, P = 3.32 × 10-2) was specific to AAs and post-traumatic stress disorder recovery (OR = 1.93, P = 7.88 × 10-5), recent antisocial behaviors (OR = 0.64, P = 2.69 × 10-3), and atheism (OR = 1.45, P = 1.34 × 10-2) were specific to EAs. Factors related to drug use comprised about half of the significant independent predictors in both AAs and EAs, with other predictors related to non-drug use behaviors, psychiatric disorders, overall health, and demographics. Conclusions: These proof-of-concept findings provide avenues for hypothesis-driven analysis, and will lead to further research on strategies to improve OUD management in EAs and AAs.

It is unknown whether vascular and metabolic diseases assessed in early adulthood are associated with Alzheimer's disease (AD) later in life.Association of AD with lipid fractions, glucose, blood pressure, body mass index (BMI), and smoking obtained prospectively from 4932 Framingham Heart Study (FHS) participants across nine quadrennial examinations was evaluated using Cox proportional hazard and Kaplan-Meier models. Age-, sex-, and education-adjusted models were tested for each factor measured at each exam and within three adult age groups (early = 35-50, middle = 51-60, and late = 61-70).A 15 mg/dL increase in high density lipoprotein (HDL) cholesterol was associated with decreased AD risk during early (15.4%, P = 0.041) and middle (17.9%, P = 0.014) adulthood. A 15 mg/dL increase in glucose measured during middle adulthood was associated with 14.5% increased AD risk (P = 0.00029). These findings remained significant after adjusting for treatment.Our findings suggest that careful management of cholesterol and glucose beginning in early adulthood can lower AD risk.

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).

Background: Peripheral inflammation is associated with increased risk for dementia. Neutrophil to lymphocyte ratio (NLR), red cell distribution width (RDW), and mean platelet volume (MPV), are easily measured circulating blood cell phenotypes reflecting chronic peripheral inflammation, but their association with dementia status is unclear. Objective: We sought to investigate the cross-sectional association of these inflammatory measures with neuropsychological (NP) test performance, and brain magnetic resonance imaging (MRI) measures in the Framingham Heart Study (FHS) Offspring, Third-generation, and Omni cohorts. Methods: We identified FHS participants who attended an exam that included a complete blood cell count (CBC) and underwent NP testing (n = 3,396) or brain MRI (n = 2,770) within five years of blood draw. We investigated the association between NLR, RDW, and MPV and NP test performance and structural MRI-derived volumetric measurements using linear mixed effect models accounting for family relationships and adjusting for potential confounders. Results: Participants were on average 60 years old, 53% female, and about 80% attended some college. Higher NLR was significantly associated with poorer performance on visual memory, and visuospatial abilities, as well as with larger white matter hyperintensity volume. We also observed associations for higher RDW with poorer executive function and smaller total cerebral brain volume. Conclusion: Chronic peripheral inflammation as measured by NLR and RDW was associated with worse cognitive function, reduced brain volume, and greater microvascular disease in FHS participants. If confirmed in other samples, CBC may provide informative and cost-effective biomarkers of abnormal brain aging in the community.

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 P 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.

Introduction: Observational studies have implicated atrial fibrillation (AF) as a risk factor for a number of cardiovascular diseases (CVD). Whether AF is causally related to these CVD is unknown. Methods: We included participants with both electronic health record-derived phenotypes and imputed genotype data in this study. A genetic instrument for AF consisting of 406 common variants was derived using a pruning and thresholding method (r2 Results: We included 615,635 participants in the study (440,690 European, 118,531 African, 48,908 Hispanic, 7,506 Asian ancestry). Genetic risk of AF was associated with heart failure in both 1-sample (OR/log odds of genetically predicted AF =1.18, 95% CI 1.15 - 1.20) and 2-sample MR (OR/log odds of genetically predicted AF =1.13, 95% CI 1.11 - 1.15). Additionally, genetic risk of AF was associated with heart failure subtypes and non-ischemic cardiomyopathy. There was no association between genetic risk of AF and pulmonary embolism (PE) or deep venous thrombosis (DVT), however, genetic risk of AF was associated with PE after excluding individuals with concurrent or prior DVT (OR1-sample MR 1.08, 95% CI 1.01 - 1.15; OR2-sample MR 1.06, 95% CI 1.03 - 1.08). Lastly, we confirmed an association between genetic risk of AF and ischemic stroke but not all-cause dementia. Our results were robust to a number of sensitivity analyses. Conclusions: In a large multi-ancestry study, we delineate the potential causal contribution of AF to a number of CVD and highlight support for a causal association between AF and isolated PE. Our findings inform how prevention and treatment of AF may affect CVD incidence and outcomes.

BackgroundIt remains unclear whether persistent loneliness is related to brain structures that are associated with cognitive decline and development of Alzheimer's disease (AD). This study aimed to investigate the relationships between different loneliness types, cognitive functioning, and regional brain volumes.MethodsLoneliness was measured longitudinally, using the item from the Center for Epidemiologic Studies Depression Scale in the Framingham Heart Study, Generation 3, with participants' average age of 46·3 ± 8·6 years. Robust regression models tested the association between different loneliness types with longitudinal neuropsychological performance (n = 2,609) and regional magnetic resonance imaging brain data (n = 1,829) (2002-2019). Results were stratified for sex, depression, and Apolipoprotein E4 (ApoE4).FindingsPersistent loneliness, but not transient loneliness, was strongly associated with cognitive decline, especially memory and executive function. Persistent loneliness was negatively associated with temporal lobe volume (β=-0.18, 95%CI [-0.32, -0.04], P=0·01). Among women, persistent loneliness was associated with smaller frontal lobe (β=-0.19, 95%CI [-0.38, -0.01], P=0·04), temporal lobe (β=-0.20, 95%CI [-0.37, -0.03], P=0·02), and hippocampus volumes (β=-0.23, 95%CI [-0.40, -0.06], P=0·007), and larger lateral ventricle volume (β=0.15, 95%CI [0.02, 0.28], P=0·03). The higher cumulative loneliness scores across three exams, the smaller parietal, temporal, and hippocampus volumes and larger lateral ventricle were evident, especially in the presence of ApoE4.InterpretationPersistent loneliness in midlife was associated with atrophy in brain regions responsible for memory and executive dysfunction. Interventions to reduce the chronicity of loneliness may mitigate the risk of age-related cognitive decline and AD.FundingUS National Institute on Aging.

With the emergence of large-scale sequencing data, methods for improving power in rare variant analyses (RVAT) are needed. Here, we show that adjusting for common variant polygenic scores improves the yield in gene-based RVAT across 65 quantitative traits in the UK Biobank (up to 20% increase at α=2.6×10−6), without a marked increase in false-positive rates or genomic inflation. Our results illustrate how adjusting for common variant effects can aid in rare variant association discovery.

Accurate and efficient classification of variant pathogenicity is critical for research and clinical care. Using data from three large studies, we demonstrate that population-based associations between rare variants and quantitative endophenotypes for three monogenic diseases (low-density-lipoprotein cholesterol for familial hypercholesterolemia, electrocardiographic QTc interval for long QT syndrome, and glycosylated hemoglobin for maturity-onset diabetes of the young) provide evidence for variant pathogenicity. Effect sizes are associated with pathogenic ClinVar assertions (P

Background: Atrial fibrillation (AF) risk estimation using clinical factors with or without genetic information may identify AF screening candidates more accurately than the guideline-based age threshold of ≥65 years. Methods: We analyzed 4 samples across the United States and Europe (derivation: UK Biobank; validation: FINRISK, Geisinger MyCode Initiative, and Framingham Heart Study). We estimated AF risk using the CHARGE-AF (Cohorts for Heart and Aging Research in Genomic Epidemiology AF) score and a combination of CHARGE-AF and a 1168-variant polygenic score (Predict-AF). We compared the utility of age, CHARGE-AF, and Predict-AF for predicting 5-year AF by quantifying discrimination and calibration. Results: Among 543 093 individuals, 8940 developed AF within 5 years. In the validation sets, CHARGE-AF (C index range, 0.720–0.824) and Predict-AF (0.749–0.831) had largely comparable discrimination, both favorable to continuous age (0.675–0.801). Calibration was similar using CHARGE-AF (slope range, 0.67–0.87) and Predict-AF (0.65–0.83). Net reclassification improvement using Predict-AF versus CHARGE-AF was modest (net reclassification improvement range, 0.024–0.057) but more favorable among individuals aged Conclusions: AF risk estimation using clinical factors may prioritize individuals for AF screening more precisely than the age threshold endorsed in current guidelines. The additional value of genetic predisposition is modest but greatest among younger individuals.

Accurate and efficient classification of variant pathogenicity is critical for research and clinical care. Using data from three large studies, we demonstrate that population-based associations between rare variants and quantitative endophenotypes for three monogenic diseases (low-density-lipoprotein cholesterol for familial hypercholesterolemia, electrocardiographic QTc interval for long QT syndrome, and glycosylated hemoglobin for maturity-onset diabetes of the young) are proxies for variant pathogenicity. Effect sizes were associated with pathogenic ClinVar assertions (P

Reproductive longevity is essential for fertility and influences healthy ageing in women1,2, but insights into its underlying biological mechanisms and treatments to preserve it are limited. Here we identify 290 genetic determinants of ovarian ageing, assessed using normal variation in age at natural menopause (ANM) in about 200,000 women of European ancestry. These common alleles were associated with clinical extremes of ANM; women in the top 1% of genetic susceptibility have an equivalent risk of premature ovarian insufficiency to those carrying monogenic FMR1 premutations3. The identified loci implicate a broad range of DNA damage response (DDR) processes and include loss-of-function variants in key DDR-associated genes. Integration with experimental models demonstrates that these DDR processes act across the life-course to shape the ovarian reserve and its rate of depletion. Furthermore, we demonstrate that experimental manipulation of DDR pathways highlighted by human genetics increases fertility and extends reproductive life in mice. Causal inference analyses using the identified genetic variants indicate that extending reproductive life in women improves bone health and reduces risk of type 2 diabetes, but increases the risk of hormone-sensitive cancers. These findings provide insight into the mechanisms that govern ovarian ageing, when they act, and how they might be targeted by therapeutic approaches to extend fertility and prevent disease. Hundreds of genetic loci associated with age at menopause, combined with experimental evidence in mice, highlight mechanisms of reproductive ageing across the lifespan.

Rationale: GWAS (Genome-Wide Association Studies) have identified hundreds of genetic loci associated with atrial fibrillation (AF). However, these loci explain only a small proportion of AF heritability. Objective: To develop an approach to identify additional AF-related genes by integrating multiple omics data. Methods and Results: Three types of omics data were integrated: (1) summary statistics from the AFGen 2017 GWAS; (2) a whole blood EWAS (Epigenome-Wide Association Study) of AF; and (3) a whole blood TWAS (Transcriptome-Wide Association Study) of AF. The variant-level GWAS results were collapsed into gene-level associations using fast set-based association analysis. The CpG-level EWAS results were also collapsed into gene-level associations by an adapted SNP-set Kernel Association Test approach. Both GWAS and EWAS gene-based associations were then meta-analyzed with TWAS using a fixed-effects model weighted by the sample size of each data set. A tissue-specific network was subsequently constructed using the NetWAS (Network-Wide Association Study). The identified genes were then compared with the AFGen 2018 GWAS that contained more than triple the number of AF cases compared with AFGen 2017 GWAS. We observed that the multiomics approach identified many more relevant AF-related genes than using AFGen 2018 GWAS alone (1931 versus 206 genes). Many of these genes are involved in the development and regulation of heart- and muscle-related biological processes. Moreover, the gene set identified by multiomics approach explained much more AF variance than those identified by GWAS alone (10.4% versus 3.5%). Conclusions: We developed a strategy to integrate multiple omics data to identify AF-related genes. Our integrative approach may be useful to improve the power of traditional GWAS, which might be particularly useful for rare traits and diseases with limited sample size.

Rationale: Genome-wide association studies have identified over 100 genetic loci for atrial fibrillation (AF); recent work described an association between loss-of-function (LOF) variants in TTN and early-onset AF. Objective: We sought to determine the contribution of rare and common genetic variation to AF risk in the general population. Methods: The UK Biobank is a population-based study of 500 000 individuals including a subset with genome-wide genotyping and exome sequencing. In this case-control study, we included AF cases and controls of genetically determined white-European ancestry; analyses were performed using a logistic mixed-effects model adjusting for age, sex, the first 4 principal components of ancestry, empirical relationships, and case-control imbalance. An exome-wide, gene-based burden analysis was performed to examine the relationship between AF and rare, high-confidence LOF variants in genes with ≥10 LOF carriers. A polygenic risk score for AF was estimated using the LDpred algorithm. We then compared the contribution of AF polygenic risk score and LOF variants to AF risk. Results: The study included 1546 AF cases and 41 593 controls. In an analysis of 9099 genes with sufficient LOF variant carriers, a significant association between AF and rare LOF variants was observed in a single gene, TTN (odds ratio, 2.71, P =2.50×10 −8 ). The association with AF was more significant (odds ratio, 6.15, P =3.26×10 −14 ) when restricting to LOF variants located in exons highly expressed in cardiac tissue ( TTN LOF ). Overall, 0.44% of individuals carried TTN LOF variants, of whom 14% had AF. Among individuals in the highest 0.44% of the AF polygenic risk score only 9.3% had AF. In contrast, the AF polygenic risk score explained 4.7% of the variance in AF susceptibility, while TTN LOF variants only accounted for 0.2%. Conclusions: Both monogenic and polygenic factors contribute to AF risk in the general population. While rare TTN LOF variants confer a substantial AF penetrance, the additive effect of many common variants explains a larger proportion of genetic susceptibility to AF.