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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.

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.

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.

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: 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.

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) are proxies for variant pathogenicity. Effect sizes were associated with pathogenic ClinVar assertions (P

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.

Background: The P-wave duration (PWD) is an electrocardiographic measurement that represents cardiac conduction in the atria. Shortened or prolonged PWD is associated with atrial fibrillation (AF). We used exome-chip data to examine the associations between common and rare variants with PWD. Methods: Fifteen studies comprising 64 440 individuals (56 943 European, 5681 African, 1186 Hispanic, 630 Asian) and ≈230 000 variants were used to examine associations with maximum PWD across the 12-lead ECG. Meta-analyses summarized association results for common variants; gene-based burden and sequence kernel association tests examined low-frequency variant-PWD associations. Additionally, we examined the associations between PWD loci and AF using previous AF genome-wide association studies. Results: We identified 21 common and low-frequency genetic loci (14 novel) associated with maximum PWD, including several AF loci ( TTN , CAND2 , SCN10A , PITX2 , CAV1 , SYNPO2L , SOX5 , TBX5, MYH6, RPL3L ). The top variants at known sarcomere genes ( TTN, MYH6 ) were associated with longer PWD and increased AF risk. However, top variants at other loci (eg, PITX2 and SCN10A ) were associated with longer PWD but lower AF risk. Conclusions: Our results highlight multiple novel genetic loci associated with PWD, and underscore the shared mechanisms of atrial conduction and AF. Prolonged PWD may be an endophenotype for several different genetic mechanisms of AF.

Our study describes breast cancer risk loci using a cross-ancestry GWAS approach. We first identify variants that are associated with breast cancer at P, GWAS have enhanced our understanding for the genetic basis of breast cancer, but the majority of them were performed for European ancestry populations. Here, the authors use a cross-ancestry approach and report seven new variants associated with breast cancer risk among women of African ancestry.

Background Biological aging estimators derived from DNA methylation data are heritable and correlate with morbidity and mortality. Consequently, identification of genetic and environmental contributors to the variation in these measures in populations has become a major goal in the field. Results Leveraging DNA methylation and SNP data from more than 40,000 individuals, we identify 137 genome-wide significant loci, of which 113 are novel, from genome-wide association study (GWAS) meta-analyses of four epigenetic clocks and epigenetic surrogate markers for granulocyte proportions and plasminogen activator inhibitor 1 levels, respectively. We find evidence for shared genetic loci associated with the Horvath clock and expression of transcripts encoding genes linked to lipid metabolism and immune function. Notably, these loci are independent of those reported to regulate DNA methylation levels at constituent clock CpGs. A polygenic score for GrimAge acceleration showed strong associations with adiposity-related traits, educational attainment, parental longevity, and C-reactive protein levels. Conclusion This study illuminates the genetic architecture underlying epigenetic aging and its shared genetic contributions with lifestyle factors and longevity.

Because studies of rare variant effects on gene expression have limited power, we investigated set-based methods to identify rare expression quantitative trait loci (eQTL) related to Alzheimer disease (AD). Gene-level and pathway-level cis rare-eQTL mapping was performed genome-wide using gene expression data derived from blood donated by 713 Alzheimer’s Disease Neuroimaging Initiative participants and from brain tissues donated by 475 Religious Orders Study/Memory and Aging Project participants. The association of gene or pathway expression with a set of all cis potentially regulatory low-frequency and rare variants within 1 Mb of genes was evaluated using SKAT-O. A total of 65 genes expressed in the brain were significant targets for rare expression single nucleotide polymorphisms (eSNPs) among which 17% (11/65) included established AD genes HLA-DRB1 and HLA-DRB5. In the blood, 307 genes were significant targets for rare eSNPs. In the blood and the brain, GNMT, LDHC, RBPMS2, DUS2, and HP were targets for significant eSNPs. Pathway enrichment analysis revealed significant pathways in the brain (n = 9) and blood (n = 16). Pathways for apoptosis signaling, cholecystokinin receptor (CCKR) signaling, and inflammation mediated by chemokine and cytokine signaling were common to both tissues. Significant rare eQTLs in inflammation pathways included five genes in the blood (ALOX5AP, CXCR2, FPR2, GRB2, IFNAR1) that were previously linked to AD. This study identified several significant gene- and pathway-level rare eQTLs, which further confirmed the importance of the immune system and inflammation in AD and highlighted the advantages of using a set-based eQTL approach for evaluating the effect of low-frequency and rare variants on gene expression.

Handgrip strength is a widely used measure of muscle strength and a predictor of a range of morbidities including cardiovascular diseases and all-cause mortality. Previous genome-wide association studies of handgrip strength have focused on common variants primarily in persons of European descent. We aimed to identify rare and ancestry-specific genetic variants associated with handgrip strength by conducting whole-genome sequence association analyses using 13,552 participants from six studies representing diverse population groups from the Trans-Omics in Precision Medicine (TOPMed) Program. By leveraging multiple handgrip strength measures performed in study participants over time, we increased our effective sample size by 7–12%. Single-variant analyses identified ten handgrip strength loci among African-Americans: four rare variants, five low-frequency variants, and one common variant. One significant and four suggestive genes were identified associated with handgrip strength when aggregating rare and functional variants; all associations were ancestry-specific. We additionally leveraged the different ancestries available in the UK Biobank to further explore the ancestry-specific association signals from the single-variant association analyses. In conclusion, our study identified 11 new loci associated with handgrip strength with rare and/or ancestry-specific genetic variations, highlighting the added value of whole-genome sequencing in diverse samples. Several of the associations identified using single-variant or aggregate analyses lie in genes with a function relevant to the brain or muscle or were reported to be associated with muscle or age-related traits. Further studies in samples with sequence data and diverse ancestries are needed to confirm these findings.

BackgroundMany human diseases are known to have a genetic contribution. While genome-wide studies have identified many disease-associated loci, it remains challenging to elucidate causal genes. In contrast, exome sequencing provides an opportunity to identify new disease genes and large-effect variants of clinical relevance. We therefore sought to determine the contribution of rare genetic variation in a curated set of human diseases and traits using a unique resource of 200,000 individuals with exome sequencing data from the UK Biobank.Methods and ResultsWe included 199,832 participants with a mean age of 68 at follow-up. Exome-wide gene-based tests were performed for 64 diseases and 23 quantitative traits using a mixed-effects model, testing rare loss-of-function and damaging missense variants. We identified 51 known and 23 novel associations with 26 diseases and traits at a false-discovery-rate of 1%. There was a striking risk associated with many Mendelian disease genes including:MYPBC3with over a 100-fold increased odds of hypertrophic cardiomyopathy,PKD1with a greater than 25-fold increased odds of chronic kidney disease, andBRCA2, BRCA1, ATMandPALB2with 3 to 10-fold increased odds of breast cancer. Notable novel findings included an association betweenGIGYF1and type 2 diabetes (OR 5.6,P=5.35×10−8), elevated blood glucose, and lower insulin-like-growth-factor-1 levels. Rare variants inCCAR2were also associated with diabetes risk (OR 13,P=8.5×10−8), whileCOL9A3was associated with cataract (OR 3.4,P=6.7×10−8). Notable associations for blood lipids and hypercholesterolemia includedNR1H3, RRBP1, GIGYF1, SCGN, APH1A, PDE3BandANGPTL8. A number of novel genes were associated with height, includingDTL, PIEZO1, SCUBE3, PAPPAandADAMTS6, whileBSNwas associated with body-mass-index. We further assessed putatively pathogenic variants in known Mendelian cardiovascular disease genes and found that between 1.3 and 2.3% of the population carried likely pathogenic variants in known cardiomyopathy, arrhythmia or hypercholesterolemia genes.ConclusionsLarge-scale population sequencing identifies known and novel genes harboring high-impact variation for human traits and diseases. A number of novel findings, includingGIGYF1,represent interesting potential therapeutic targets. Exome sequencing at scale can identify a meaningful proportion of the population that carries a pathogenic variant underlying cardiovascular disease.

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 5,257 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 1Mb 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 expression of “proxy” genes that discriminate particular cell type. Ct-eQTL analysis identified 11,649 and 2,533 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 1Mb 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.

Mechanisms underlying the protective effect of apolipoprotein E (APOE) ε2 against Alzheimer’s disease (AD) are not well understood. We analyzed gene expression data derived from autopsied brains donated by 982 individuals including 135 APOE ε 2/ε 3 carriers. Complement pathway genes C4A and C4B were among the most significantly differentially expressed genes between ε 2/ε 3 AD cases and controls. We also identified an APOE ε2/ε3 AD-specific co-expression network enriched for astrocytes, oligodendrocytes and oligodendrocyte progenitor cells containing the genes C4A, C4B, and HSPA2. These genes were significantly associated with the ratio of phosphorylated tau at position 231 to total Tau but not with amyloid-β 42 level, suggesting this APOE ε 2 related co-expression network may primarily be involved with tau pathology. HSPA2 expression was oligodendrocyte specific and significantly associated with C4B protein. Our findings provide the first evidence of a crucial role of the complement pathway in the protective effect of APOE ε2 for AD.

Biological ageing estimators derived from DNA methylation (DNAm) data are heritable and correlate with morbidity and mortality. Leveraging DNAm and SNP data from >41,000 individuals, we identify 137 genome-wide significant loci (113 novel) from meta-analyses of four epigenetic clocks and epigenetic surrogate markers for granulocyte proportions and plasminogen activator inhibitor 1 levels, respectively. We report strong genetic correlations with longevity and lifestyle factors such as smoking, education, and obesity. Significant associations are observed in polygenic risk score analysis and to a lesser extent in Mendelian randomization analyses. This study illuminates the genetic architecture underlying epigenetic ageing and its shared genetic contributions with lifestyle factors and longevity.

The Alzheimer’s Disease Sequencing Project (ADSP) undertook whole exome sequencing in 5,740 late-onset Alzheimer disease (AD) cases and 5,096 cognitively normal controls primarily of European ancestry (EA), among whom 218 cases and 177 controls were Caribbean Hispanic (CH). An age-, sex- and APOE based risk score and family history were used to select cases most likely to harbor novel AD risk variants and controls least likely to develop AD by age 85 years. We tested ~1.5 million single nucleotide variants (SNVs) and 50,000 insertion-deletion polymorphisms (indels) for association to AD, using multiple models considering individual variants as well as gene-based tests aggregating rare, predicted functional, and loss of function variants. Sixteen single variants and 19 genes that met criteria for significant or suggestive associations after multiple-testing correction were evaluated for replication in four independent samples; three with whole exome sequencing (2,778 cases, 7,262 controls) and one with genome-wide genotyping imputed to the Haplotype Reference Consortium panel (9,343 cases, 11,527 controls). The top findings in the discovery sample were also followed-up in the ADSP whole-genome sequenced family-based dataset (197 members of 42 EA families and 501 members of 157 CH families). We identified novel and predicted functional genetic variants in genes previously associated with AD. We also detected associations in three novel genes: IGHG3 (p = 9.8 × 10−7), an immunoglobulin gene whose antibodies interact with β-amyloid, a long non-coding RNA AC099552.4 (p = 1.2 × 10−7), and a zinc-finger protein ZNF655 (gene-based p = 5.0 × 10−6). The latter two suggest an important role for transcriptional regulation in AD pathogenesis.

Lipoprotein(a), Lp(a), is a modified low-density lipoprotein particle that contains apolipoprotein(a), encoded by LPA, and is a highly heritable, causal risk factor for cardiovascular diseases that varies in concentrations across ancestries. Here, we use deep-coverage whole genome sequencing in 8392 individuals of European and African ancestry to discover and interpret both single-nucleotide variants and copy number (CN) variation associated with Lp(a). We observe that genetic determinants between Europeans and Africans have several unique determinants. The common variant rs12740374 associated with Lp(a) cholesterol is an eQTL for SORT1 and independent of LDL cholesterol. Observed associations of aggregates of rare non-coding variants are largely explained by LPA structural variation, namely the LPA kringle IV 2 (KIV2)-CN. Finally, we find that LPA risk genotypes confer greater relative risk for incident atherosclerotic cardiovascular diseases compared to directly measured Lp(a), and are significantly associated with measures of subclinical atherosclerosis in African Americans., Circulating lipoprotein(a) is an important risk factor for cardiovascular disease and shows variability between different ethnic groups. Here, Zekavat et al. perform whole-genome sequencing in individuals of European and African ancestries and find ancestry-specific genetic determinants for lipoprotein(a) levels.

Background MicroRNAs (miRNAs) regulate gene expression and influence cancer. Primary transcripts of miRNAs (pri-miRNAs) are poorly annotated and little is known about the role of germline variation in miRNA genes and breast cancer (BC). We sought to identify germline miRNA variants associated with BC risk and tumor subtype among African-American (AA) women. Methods Under the African American Breast Cancer Epidemiology and Risk (AMBER) Consortium, genotyping and imputed data from four studies on BC in AA women were combined into a final dataset containing 224,188 miRNA gene single nucleotide polymorphisms (SNPs) for 8350 women: 3663 cases and 4687 controls. The primary miRNA sequence was identified for 566 miRNA genes expressed in Encyclopedia of DNA Elements (ENCODE) Tier 1 cell types and human pancreatic islets. Association analysis was conducted using logistic regression for BC status overall and by tumor subtype. Results A novel BC signal was localized to an 8.6-kb region of 17q25.3 by four SNPs (rs9913477, rs1428882938, rs28585511, and rs7502931) and remained statistically significant after multiple test correction (odds ratio (OR) = 1.44, 95% confidence interval (CI) = 1.26–1.65; p = 3.15 × 10−7; false discovery rate (FDR) = 0.03). These SNPs reside in a genomic location that includes both the predicted primary transcript of the noncoding miRNA gene MIR3065 and the first intron of the gene for brain-specific angiogenesis inhibitor 1-associated protein 2 (BAIAP2). Furthermore, miRNA-associated SNPs on chromosomes 1p32.3, 5q32, and 3p25.1 were the strongest signals for hormone receptor, luminal versus basal-like, and HER2 enrichment status, respectively. A second phase of genotyping (1397 BC cases, 2418 controls) that included two SNPs in the 8.6-kb region was used for validation and meta-analysis. While neither rs4969239 nor rs9913477 was validated, when meta-analyzed with the original dataset their association with BC remained directionally consistent (OR = 1.29, 95% CI = 1.16–1.44 (p = 4.18 × 10–6) and OR = 1.33, 95% CI = 1.17–1.51 (p = 1.6 × 10–5), respectively). Conclusion Germline genetic variation indicates that MIR3065 may play an important role in BC development and heterogeneity among AA women. Further investigation to determine the potential functional effects of these SNPs is warranted. This study contributes to our understanding of BC risk in AA women and highlights the complexity in evaluating variation in gene-dense regions of the human genome.

Background: Atrial fibrillation (AF) has a substantial genetic basis. Identification of individuals at greatest AF risk could minimize the incidence of cardioembolic stroke. Methods: To determine whether genetic data can stratify risk for development of AF, we examined associations between AF genetic risk scores and incident AF in 5 prospective studies comprising 18 919 individuals of European ancestry. We examined associations between AF genetic risk scores and ischemic stroke in a separate study of 509 ischemic stroke cases (202 cardioembolic [40%]) and 3028 referents. Scores were based on 11 to 719 common variants (≥5%) associated with AF at P values ranging from −3 to −8 in a prior independent genetic association study. Results: Incident AF occurred in 1032 individuals (5.5%). AF genetic risk scores were associated with new-onset AF after adjustment for clinical risk factors. The pooled hazard ratio for incident AF for the highest versus lowest quartile of genetic risk scores ranged from 1.28 (719 variants; 95% confidence interval, 1.13–1.46; P =1.5×10 −4 ) to 1.67 (25 variants; 95% confidence interval, 1.47–1.90; P =9.3×10 −15 ). Discrimination of combined clinical and genetic risk scores varied across studies and scores (maximum C statistic, 0.629–0.811; maximum ΔC statistic from clinical score alone, 0.009–0.017). AF genetic risk was associated with stroke in age- and sex-adjusted models. For example, individuals in the highest versus lowest quartile of a 127-variant score had a 2.49-fold increased odds of cardioembolic stroke (95% confidence interval, 1.39–4.58; P =2.7×10 −3 ). The effect persisted after the exclusion of individuals (n=70) with known AF (odds ratio, 2.25; 95% confidence interval, 1.20–4.40; P =0.01). Conclusions: Comprehensive AF genetic risk scores were associated with incident AF beyond associations for clinical AF risk factors but offered small improvements in discrimination. AF genetic risk was also associated with cardioembolic stroke in age- and sex-adjusted analyses. Efforts are warranted to determine whether AF genetic risk may improve identification of subclinical AF or help distinguish between stroke mechanisms.

Publisher's version (útgefin grein)., Human longevity is heritable, but genome-wide association (GWA) studies have had limited success. Here, we perform two meta-analyses of GWA studies of a rigorous longevity phenotype definition including 11,262/3484 cases surviving at or beyond the age corresponding to the 90th/99th survival percentile, respectively, and 25,483 controls whose age at death or at last contact was at or below the age corresponding to the 60th survival percentile. Consistent with previous reports, rs429358 (apolipoprotein E (ApoE) ε4) is associated with lower odds of surviving to the 90th and 99th percentile age, while rs7412 (ApoE ε2) shows the opposite. Moreover, rs7676745, located near GPR78, associates with lower odds of surviving to the 90th percentile age. Gene-level association analysis reveals a role for tissue-specific expression of multiple genes in longevity. Finally, genetic correlation of the longevity GWA results with that of several disease-related phenotypes points to a shared genetic architecture between health and longevity., Alexander von Humboldt-Stiftung

Each additional copy of the apolipoprotein E4 (APOE4) allele is associated with a higher risk of Alzheimer’s dementia, while the APOE2 allele is associated with a lower risk of Alzheimer’s dementia, it is not yet known whether APOE2 homozygotes have a particularly low risk. We generated Alzheimer’s dementia odds ratios and other findings in more than 5,000 clinically characterized and neuropathologically characterized Alzheimer’s dementia cases and controls. APOE2/2 was associated with a low Alzheimer’s dementia odds ratios compared to APOE2/3 and 3/3, and an exceptionally low odds ratio compared to APOE4/4, and the impact of APOE2 and APOE4 gene dose was significantly greater in the neuropathologically confirmed group than in more than 24,000 neuropathologically unconfirmed cases and controls. Finding and targeting the factors by which APOE and its variants influence Alzheimer’s disease could have a major impact on the understanding, treatment and prevention of the disease., APOE is the major genetic risk factor for Alzheimer’s disease. In a large number of neuropathologically confirmed cases and controls, the impact of different APOE genotypes on Alzheimer’s dementia risk was greater than previously thought and APOE2 homozygotes had an exceptionally low risk.

Aim: We compared the performance of multiple testing corrections for candidate gene methylation studies, namely Sidak (accurate Bonferroni), false-discovery rate and three adjustments that incorporate the correlation between CpGs: extreme tail theory (ETT), Gao et al. (GEA), and Li and Ji methods. Materials & methods: The experiment-wide type 1 error rate was examined in simulations based on Illumina EPIC and 450K data. Results: For high-correlation genes, Sidak and false-discovery rate corrections were conservative while the Li and Ji method was liberal. The GEA method tended to be conservative unless a threshold parameter was adjusted. The ETT yielded an appropriate type 1 error rate. Conclusion: For genes with substantial correlation across measured CpGs, GEA and ETT can appropriately correct for multiple testing in candidate gene methylation studies.

We hypothesize that mechanisms associated with extended reproductive age may overlap with mechanisms for the selection of genetic variants that slow aging and decrease risk for age-related diseases. Therefore, the goal of this analysis is to search for genetic variants associated with delayed age of menopause (AOM) among women in a study of familial longevity.We performed a meta-analysis of genome-wide association studies for AOM in 1,286 women in the Long Life Family Study (LLFS) and 3,151 women in the Health and Retirement Study, and then sought replication in the Framingham Heart Study (FHS). We used Cox proportional hazard regression of AOM to account for censoring, with a robust variance estimator to adjust for within familial relations.In the meta-analysis, a single nucleotide polymorphism (SNP) previously associated with AOM reached genome-wide significance (rs16991615; HR = 0.74, P = 6.99 × 10). A total of 35 variants reached10 level of significance and replicated in the FHS and in a 2015 large meta-analysis (ReproGen Consortium). We also identified several novel SNPs associated with AOM including rs3094005: MICB, rs13196892: TXNDC5 | MUTED, rs72774935: SSBP2 | ATG10, rs9447453: COL12A1, rs114298934: FHL2 | NCK2, rs6467223: TNPO3, rs9666274 and rs10766593: NAV2, and rs7281846: HSPA13.This work indicates novel associations and replicates known associations between genetic variants and AOM. A number of these associations make sense for their roles in aging.Supplemental Digital Content 1, http://links.lww.com/MENO/A420.

CpG‐related single nucleotide polymorphisms (CGS) have the potential to perturb DNA methylation; however, their effects on Alzheimer disease (AD) risk have not been evaluated systematically. We conducted a genome‐wide association study using a sliding‐window approach to measure the combined effects of CGSes on AD risk in a discovery sample of 24 European ancestry cohorts (12,181 cases, 12,601 controls) from the Alzheimer's Disease Genetics Consortium (ADGC) and replication sample of seven European ancestry cohorts (7,554 cases, 27,382 controls) from the International Genomics of Alzheimer's Project (IGAP). The potential functional relevance of significant associations was evaluated by analysis of methylation and expression levels in brain tissue of the Religious Orders Study and the Rush Memory and Aging Project (ROSMAP), and in whole blood of Framingham Heart Study participants (FHS). Genome‐wide significant (p

Birth weight (BW) variation is influenced by fetal and maternal genetic and non-genetic factors, and has been reproducibly associated with future cardio-metabolic health outcomes. These associations have been proposed to reflect the lifelong consequences of an adverse intrauterine environment. In earlier work, we demonstrated that much of the negative correlation between BW and adult cardio-metabolic traits could instead be attributable to shared genetic effects. However, that work and other previous studies did not systematically distinguish the direct effects of an individual’s own genotype on BW and subsequent disease risk from indirect effects of their mother’s correlated genotype, mediated by the intrauterine environment. Here, we describe expanded genome-wide association analyses of own BW (n=321,223) and offspring BW (n=230,069 mothers), which identified 278 independent association signals influencing BW (214 novel). We used structural equation modelling to decompose the contributions of direct fetal and indirect maternal genetic influences on BW, implicating fetal- and maternal-specific mechanisms. We used Mendelian randomization to explore the causal relationships between factors influencing BW through fetal or maternal routes, for example, glycemic traits and blood pressure. Direct fetal genotype effects dominate the shared genetic contribution to the association between lower BW and higher type 2 diabetes risk, whereas the relationship between lower BW and higher later blood pressure (BP) is driven by a combination of indirect maternal and direct fetal genetic effects: indirect effects of maternal BP-raising genotypes act to reduce offspring BW, but only direct fetal genotype effects (once inherited) increase the offspring’s later BP. Instrumental variable analysis using maternal BW-lowering genotypes to proxy for an adverse intrauterine environment provided no evidence that it causally raises offspring BP. In successfully separating fetal from maternal genetic effects, this work represents an important advance in genetic studies of perinatal outcomes, and shows that the association between lower BW and higher adult BP is attributable to genetic effects, and not to intrauterine programming.

Emerging evidence suggests that the basis for variation in late-life mobility is attributable, in part, to genetic factors, which may become increasingly important with age. Our objective was to systematically assess the contribution of genetic variation to gait speed in older individuals. We conducted a meta-analysis of gait speed GWASs in 31,478 older adults from 17 cohorts of the CHARGE consortium, and validated our results in 2,588 older adults from 4 independent studies. We followed our initial discoveries with network and eQTL analysis of candidate signals in tissues. The meta-analysis resulted in a list of 536 suggestive genome wide significant SNPs in or near 69 genes. Further interrogation with Pathway Analysis placed gait speed as a polygenic complex trait in five major networks. Subsequent eQTL analysis revealed several SNPs significantly associated with the expression of PRSS16, WDSUB1 and PTPRT, which in addition to the meta-analysis and pathway suggested that genetic effects on gait speed may occur through synaptic function and neuronal development pathways. No genome-wide significant signals for gait speed were identified from this moderately large sample of older adults, suggesting that more refined physical function phenotypes will be needed to identify the genetic basis of gait speed in aging.

Leveraging population-distinct linkage equilibrium (LD) patterns, trans-ethnic follow-up of variants discovered from genome-wide association studies (GWAS) has proved to be useful in facilitating the identification of bona fide causal variants. We previously developed the preferential LD approach, a novel method that successfully identified causal variants driving the GWAS signals within European-descent populations even when the causal variants were only weakly linked with the GWAS-discovered variants. To evaluate the performance of our approach in a trans-ethnic setting, we applied it to follow up breast cancer GWAS hits identified mostly from populations of European ancestry in African Americans (AA). We evaluated 74 breast cancer GWAS variants in 8,315 AA women from the African American Breast Cancer Epidemiology and Risk (AMBER) consortium. Only 27% of them were associated with breast cancer risk at significance level α=0.05, suggesting race-specificity of the identified breast cancer risk loci. We followed up on those replicated GWAS hits in the AMBER consortium utilizing the preferential LD approach, to search for causal variants or better breast cancer markers from the 1000 Genomes variant catalog. Our approach identified stronger breast cancer markers for 80% of the GWAS hits with at least nominal breast cancer association, and in 81% of these cases, the marker identified was among the top 10 of all 1000 Genomes variants in the corresponding locus. The results support trans-ethnic application of the preferential LD approach in search for candidate causal variants, and may have implications for future genetic research of breast cancer in AA women.

A large percentage of breast cancer heritability remains unaccounted for, and most of the known susceptibility loci have been established in European and Asian populations. Rare variants may contribute to the unexplained heritability of this disease, including in women of African ancestry (AA). We conducted an exome-wide analysis of rare variants in relation to risk of overall and subtype-specific breast cancer in the African American Breast Cancer Epidemiology and Risk (AMBER) Consortium, which includes data from four large studies of AA women. Genotyping on the Illumina Human Exome Beadchip yielded data for 170 812 SNPs and 8287 subjects: 3629 cases (1093 estrogen receptor negative (ER-), 1968 ER+, 568 ER unknown) and 4658 controls, the largest exome chip study to date for AA breast cancer. Pooled gene-based association analyses were performed using the unified optimal sequence kernel association test (SKAT-O) for variants with minor allele frequency (MAF) ≤ 5%. In addition, each variant with MAF >0.5% was tested for association using logistic regression. There were no significant associations with overall breast cancer. However, a novel gene, FBXL22 (P = 8.2×10(-6)), and a gene previously identified in GWAS of European ancestry populations, PDE4D (P = 1.2×10(-6)), were significantly associated with ER- breast cancer after correction for multiple testing. Cases with the associated rare variants were also negative for progesterone and human epidermal growth factor receptors-thus, triple-negative cancer. Replication is required to confirm these gene-level associations, which are based on very small counts at extremely rare SNPs.

Importance Compared with non-Hispanic White individuals, African American individuals from the same community are approximately twice as likely to develop Alzheimer disease. Despite this disparity, the largest Alzheimer disease genome-wide association studies to date have been conducted in non-Hispanic White individuals. In the largest association analyses of Alzheimer disease in African American individuals,ABCA7,TREM2, and an intergenic locus at 5q35 were previously implicated. Objective To identify additional risk loci in African American individuals by increasing the sample size and using the African Genome Resource panel. Design, Setting, and Participants This genome-wide association meta-analysis used case-control and family-based data sets from the Alzheimer Disease Genetics Consortium. There were multiple recruitment sites throughout the United States that included individuals with Alzheimer disease and controls of African American ancestry. Analysis began October 2018 and ended September 2019. Main Outcomes and Measures Diagnosis of Alzheimer disease. Results A total of 2784 individuals with Alzheimer disease (1944 female [69.8%]) and 5222 controls (3743 female [71.7%]) were analyzed (mean [SD] age at last evaluation, 74.2 [13.6] years). Associations with 4 novel common loci centered near the intracellular glycoprotein trafficking geneEDEM1(3p26;P = 8.9 × 10−7), near the immune response geneALCAM(3q13;P = 9.3 × 10−7), withinGPC6(13q31;P = 4.1 × 10−7), a gene critical for recruitment of glutamatergic receptors to the neuronal membrane, and withinVRK3(19q13.33;P = 3.5 × 10−7), a gene involved in glutamate neurotoxicity, were identified. In addition, several loci associated with rare variants, including a genome-wide significant intergenic locus nearIGF1Rat 15q26 (P = 1.7 × 10−9) and 6 additional loci with suggestive significance (P ≤ 5 × 10−7) such asAPI5 at 11p12 (P = 8.8 × 10−8) andRBFOX1at 16p13 (P = 5.4 × 10−7) were identified. Gene expression data from brain tissue demonstrate association ofALCAM, ARAP1, GPC6, andRBFOX1with brain β-amyloid load. Of 25 known loci associated with Alzheimer disease in non-Hispanic White individuals, onlyAPOE,ABCA7,TREM2,BIN1,CD2AP,FERMT2, andWWOXwere implicated at a nominal significance level or stronger in African American individuals. Pathway analyses strongly support the notion that immunity, lipid processing, and intracellular trafficking pathways underlying Alzheimer disease in African American individuals overlap with those observed in non-Hispanic White individuals. A new pathway emerging from these analyses is the kidney system, suggesting a novel mechanism for Alzheimer disease that needs further exploration. Conclusions and Relevance While the major pathways involved in Alzheimer disease etiology in African American individuals are similar to those in non-Hispanic White individuals, the disease-associated loci within these pathways differ.

Emerging evidence suggests that the basis for variation in late-life mobility is attributable, in part, to genetic factors, which may become increasingly important with age. Our objective was to systematically assess the contribution of genetic variation to gait speed in older individuals. We conducted a meta-analysis of gait speed GWASs in 31,478 older adults from 17 cohorts of the CHARGE consortium, and validated our results in 2,588 older adults from 4 independent studies. We followed our initial discoveries with network and eQTL analysis of candidate signals in tissues. The meta-analysis resulted in a list of 536 suggestive genome wide significant SNPs in or near 69 genes. Further interrogation with Pathway Analysis placed gait speed as a polygenic complex trait in five major networks. Subsequent eQTL analysis revealed several SNPs significantly associated with the expression of PRSS16, WDSUB1 and PTPRT, which in addition to the meta-analysis and pathway suggested that genetic effects on gait speed may occur through synaptic function and neuronal development pathways. No genome-wide significant signals for gait speed were identified from this moderately large sample of older adults, suggesting that more refined physical function phenotypes will be needed to identify the genetic basis of gait speed in aging.

Background: To date, most genome-wide association studies (GWAS) of breast cancer have been conducted only among women of Asian and European ancestry. It is difficult to generalize results from those studies to women of African ancestry (AA). We conducted a large genetic association study of breast cancer in women of AA by analyzing both genetic and transcriptomic data. Methods: This collaborative study included 11,073 cases and 11,095 controls of AA who were participants in more than 15 studies conducted in the U.S. and Africa. Genotyping data were harmonized and imputed using the 1000 Genomes Project database as the reference. Imputed genotypes were used for GWAS to identify novel genetic risk loci for breast cancer. To search for susceptibility genes, we conducted a transcriptome-wide association study (TWAS), in which gene expression prediction models were built using genetic and tumor tissue RNA sequencing data from ~400 AA patients and used to impute expression levels of genes across the transcriptome for association analyses in all cases and controls included in the GWAS mentioned above. Results: We identified five loci (5p15.33, 5q31.3, 10q26.13, 18q12.1, and 19p13.11) associated with breast cancer risk at P < 5 × 10−8, including a novel locus at 5q31.3 (allelic odds ratio, OR = 1.18, 95% CI = 1.11-1.25, P = 4.65 × 10−8, nearby gene, ARHGAP26). This locus was also identified in association with estrogen receptor (ER) positive breast cancer at P < 5 × 10−8. Analyses stratified by ER status replicated known loci associated specifically with ER-positive (10q26.13) or ER-negative (2q14.2, 2p11.2, 5p15.33) breast cancer at P < 5 × 10−8. Of the 165 lead risk SNPs reported from previous breast cancer GWAS, 35 SNPs were replicated with the same association direction at P < 0.05. We constructed a polygenic risk score using these 35 replicated SNPs and the lead risk SNP at the novel locus and estimated the AUC to be 0.575. Of the 7,592 genes tested in the TWAS, we identified one gene, AC091053.1, with an association at a Bonferroni-corrected threshold of 6.64 × 10−6 (0.05/7,592). AC091053.1 is a long non-coding RNA gene at locus 11p15.4, where no risk variants have been identified in any previous breast cancer GWAS. AC091053.1 is located in the region of protein coding gene DENND2B, which acts as a regulator of MAPK1/ERK2 kinase and reduces the tumorigenic phenotype in cells. The gene AC091053.1 was associated with ER-positive breast cancer with P = 4.11 × 10−5 and ER-negative breast cancer with P = 0.032. Conclusions: Our study, the largest genetic study conducted to date in AA, identified novel breast cancer risk loci at 5q31.3 and 11p15.4 (AC091053.1) among women of AA and replicated >30 associations reported in previous studies. Studies with a larger sample size are needed to further investigate genetic variants and genes associated with breast cancer risk in AA women. Citation Format: Guochong Jia, Jie Ping, Yaohua Yang, Maureen Sanderson, Qiuyin Cai, Xingyi Guo, William J. Blot, Bingshan Li, Elisa V. Bandera, Manjeet K. Bolla, Montserrat García-Closas, Douglas F. Easton, Mary K. Fadden, Jian Gu, Dezheng Huo, Esther M. John, Kathryn L. Lunetta, Olufunmilayo I. Olopade, Xiang Shu, Melissa A. Troester, Song Yao, Breast Cancer Association Consortium, Andrew F. Olshan, Christine B. Ambrosone, Christopher A. Haiman, Jirong Long, Julie R. Palmer, Wei Zheng. Integrating genomic and transcriptomic data to identify genetic loci associated with breast cancer risk in women of African ancestry [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 28.

The genetic architecture of late-onset Alzheimer disease (AD) in African Americans (AAs) differs from that in persons of European ancestry. In addition to APOE, genome-wide association studies (GWASs) of AD in AA samples have implicated ABCA7, COBL, and SLC10A2 as AA-AD risk genes. Previously, we identified by whole exome sequencing a small number of AA AD cases and subsequent genotyping in a large AA sample of AD cases and controls association of AD risk with a pair of rare missense variants in AKAP9. In this study, we performed targeted deep sequencing (including both introns and exons) of approximately 100 genes previously linked to AD or AD-related traits in an AA cohort of 489 AD cases and 472 controls to find novel AD risk variants. We observed association with an 11 base-pair frame-shift loss-of-function (LOF) variant in ABCA7 (rs567222111) for which the evidence was bolstered when combined with data from a replication AA cohort of 484 cases and 484 controls (OR = 2.42, p = 0.022). We also found association of AD with a rare 9 bp deletion (rs371245265) located very close to the AKAP9 transcription start site (rs371245265, OR = 10.75, p = 0.0053). The most significant findings were obtained with a rare protective variant in F5 (OR = 0.053, p = 6.40 × 10-5), a gene that was previously associated with a brain MRI measure of hippocampal atrophy, and two common variants in KIAA0196 (OR = 1.51, p

Multiple breast cancer loci have been identified in previous genome-wide association studies, but they were mainly conducted in populations of European ancestry. Women of African ancestry are more likely to have young-onset and oestrogen receptor (ER) negative breast cancer for reasons that are unknown and understudied. To identify genetic risk factors for breast cancer in women of African descent, we conducted a meta-analysis of two genome-wide association studies of breast cancer; one study consists of 1,657 cases and 2,029 controls genotyped with Illumina's HumanOmni2.5 BeadChip and the other study included 3,016 cases and 2,745 controls genotyped using Illumina Human1M-Duo BeadChip. The top 18,376 single nucleotide polymorphisms (SNP) from the meta-analysis were replicated in the third study that consists of 1,984 African Americans cases and 2,939 controls. We found that SNP rs13074711, 26.5 Kb upstream of TNFSF10 at 3q26.21, was significantly associated with risk of oestrogen receptor (ER)-negative breast cancer (odds ratio [OR]=1.29, 95% CI: 1.18-1.40; P = 1.8 × 10 (-) (8)). Functional annotations suggest that the TNFSF10 gene may be involved in breast cancer aetiology, but further functional experiments are needed. In addition, we confirmed SNP rs10069690 was the best indicator for ER-negative breast cancer at 5p15.33 (OR = 1.30; P = 2.4 × 10 (-) (10)) and identified rs12998806 as the best indicator for ER-positive breast cancer at 2q35 (OR = 1.34; P = 2.2 × 10 (-) (8)) for women of African ancestry. These findings demonstrated additional susceptibility alleles for breast cancer can be revealed in diverse populations and have important public health implications in building race/ethnicity-specific risk prediction model for breast cancer.

BACKGROUND: The Healthy Aging Index (HAI) is a tool for measuring the extent of health and disease across multiple systems. METHODS: We conducted a genome-wide association study and a genome-wide linkage analysis to map quantitative trait loci associated with the HAI and a modified HAI weighted for mortality risk in 3,140 individuals selected for familial longevity from the Long Life Family Study. The genome-wide association study used the Long Life Family Study as the discovery cohort and individuals from the Cardiovascular Health Study and the Framingham Heart Study as replication cohorts. RESULTS: There were no genome-wide significant findings from the genome-wide association study; however, several single-nucleotide polymorphisms near ZNF704 on chromosome 8q21.13 were suggestively associated with the HAI in the Long Life Family Study (p < 10(-) (6)) and nominally replicated in the Cardiovascular Health Study and Framingham Heart Study. Linkage results revealed significant evidence (log-odds score = 3.36) for a quantitative trait locus for mortality-optimized HAI in women on chromosome 9p24-p23. However, results of fine-mapping studies did not implicate any specific candidate genes within this region of interest. CONCLUSIONS: ZNF704 may be a potential candidate gene for studies of the genetic underpinnings of longevity. BACKGROUND: The Healthy Aging Index (HAI) is a tool for measuring the extent of health and disease across multiple systems.METHODS: We conducted a genome-wide association study and a genome-wide linkage analysis to map quantitative trait loci associated with the HAI and a modified HAI weighted for mortality risk in 3,140 individuals selected for familial longevity from the Long Life Family Study. The genome-wide association study used the Long Life Family Study as the discovery cohort and individuals from the Cardiovascular Health Study and the Framingham Heart Study as replication cohorts.RESULTS: There were no genome-wide significant findings from the genome-wide association study; however, several single-nucleotide polymorphisms near ZNF704 on chromosome 8q21.13 were suggestively associated with the HAI in the Long Life Family Study (p < 10(-) (6)) and nominally replicated in the Cardiovascular Health Study and Framingham Heart Study. Linkage results revealed significant evidence (log-odds score = 3.36) for a quantitative trait locus for mortality-optimized HAI in women on chromosome 9p24-p23. However, results of fine-mapping studies did not implicate any specific candidate genes within this region of interest.CONCLUSIONS: ZNF704 may be a potential candidate gene for studies of the genetic underpinnings of longevity.

Atrial fibrillation (AF) affects more than 33 million individuals worldwide 1 and has a complex heritability 2 . We conducted the largest meta-analysis of genome-wide association studies (GWAS) for AF to date, consisting of more than half a million individuals, including 65,446 with AF. In total, we identified 97 loci significantly associated with AF, including 67 that were novel in a combined-ancestry analysis, and 3 that were novel in a European-specific analysis. We sought to identify AF-associated genes at the GWAS loci by performing RNA-sequencing and expression quantitative trait locus analyses in 101 left atrial samples, the most relevant tissue for AF. We also performed transcriptome-wide analyses that identified 57 AF-associated genes, 42 of which overlap with GWAS loci. The identified loci implicate genes enriched within cardiac developmental, electrophysiological, contractile and structural pathways. These results extend our understanding of the biological pathways underlying AF and may facilitate the development of therapeutics for AF.

Background/Aims: The Alzheimer’s Disease Sequencing Project (ADSP) aims to identify novel genes influencing Alzheimer’s disease (AD). Variants within genes known to cause dementias other than AD have previously been associated with AD risk. We describe evidence of co-segregation and associations between variants in dementia genes and clinically diagnosed AD within the ADSP. Methods: We summarize the properties of known pathogenic variants within dementia genes, describe the co-segregation of variants annotated as “pathogenic” in ClinVar and new candidates observed in ADSP families, and test for associations between rare variants in dementia genes in the ADSP case-control study. The participants were clinically evaluated for AD, and they represent European, Caribbean Hispanic, and isolate Dutch populations. Results/Conclusions: Pathogenic variants in dementia genes were predominantly rare and conserved coding changes. Pathogenic variants within ARSA, CSF1R, and GRN were observed, and candidate variants in GRN and CHMP2B were nominated in ADSP families. An independent case-control study provided evidence of an association between variants in TREM2, APOE, ARSA, CSF1R, PSEN1, and MAPT and risk of AD. Variants in genes which cause dementing disorders may influence the clinical diagnosis of AD in a small proportion of cases within the ADSP.

© 2015, Elsevier Inc. All rights reserved. Background: Late-onset Alzheimer's disease (AD) is heritable with 20 genes showing genome-wide association in the International Genomics of Alzheimer's Project (IGAP). To identify the biology underlying the disease, we extended these genetic data in a pathway analysis. Methods: The ALIGATOR and GSEA algorithms were used in the IGAP data to identify associated functional pathways and correlated gene expression networks in human brain. Results: ALIGATOR identified an excess of curated biological pathways showing enrichment of association. Enriched areas of biology included the immune response (P = 3.27 × 10-12 after multiple testing correction for pathways), regulation of endocytosis (P = 1.31 × 10-11), cholesterol transport (P = 2.96 × 10-9), and proteasome-ubiquitin activity (P = 1.34 × 10-6). Correlated gene expression analysis identified four significant network modules, all related to the immune response (corrected P =.002-.05). Conclusions: The immune response, regulation of endocytosis, cholesterol transport, and protein ubiquitination represent prime targets for AD therapeutics., Medical Research Council, Alzheimer’s Research UK, and theWelsh Assembly Government. ADGC and CHARGE were supported by the National Institutes of Health, National Institute on Aging (NIH-NIA). CHARGE was also supported by Erasmus Medical Center and Erasmus University. IGAP was funded by the French National Foundation on Alzheimer’s Disease and Related Disorders, the Centre National de Genotypage and the Institut Pasteur de Lille, Inserm, FRC (Fondation pour la Recherche sur le Cerveau), and Rotary. This work has been developed and supported by the LABEX (Laboratory of Excellence Program Investment for the Future) DISTALZ grant (Development of Innovative Strategies for a Transdisciplinary approach to ALZheimer’s disease).

Background— Previous reports have implicated multiple genetic loci associated with AF, but the contributions of genome-wide variation to AF susceptibility have not been quantified. Methods and Results— We assessed the contribution of genome-wide single-nucleotide polymorphism variation to AF risk (single-nucleotide polymorphism heritability, h 2 g ) using data from 120 286 unrelated individuals of European ancestry (2987 with AF) in the population-based UK Biobank. We ascertained AF based on self-report, medical record billing codes, procedure codes, and death records. We estimated h 2 g using a variance components method with variants having a minor allele frequency ≥1%. We evaluated h 2 g in age, sex, and genomic strata of interest. The h 2 g for AF was 22.1% (95% confidence interval, 15.6%–28.5%) and was similar for early- versus older-onset AF (≤65 versus >65 years of age), as well as for men and women. The proportion of AF variance explained by genetic variation was mainly accounted for by common (minor allele frequency, ≥5%) variants (20.4%; 95% confidence interval, 15.1%–25.6%). Only 6.4% (95% confidence interval, 5.1%–7.7%) of AF variance was attributed to variation within known AF susceptibility, cardiac arrhythmia, and cardiomyopathy gene regions. Conclusions— Genetic variation contributes substantially to AF risk. The risk for AF conferred by genomic variation is similar to that observed for several other cardiovascular diseases. Established AF loci only explain a moderate proportion of disease risk, suggesting that further genetic discovery, with an emphasis on common variation, is warranted to understand the causal genetic basis of AF.