Publications by authors named "Kathryn L Lunetta"

198 Publications

Cell-type-specific expression quantitative trait loci associated with Alzheimer disease in blood and brain tissue.

Transl Psychiatry 2021 Apr 27;11(1):250. Epub 2021 Apr 27.

Bioinformatics Graduate Program, Boston University, Boston, MA, USA.

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.
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http://dx.doi.org/10.1038/s41398-021-01373-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8079392PMC
April 2021

Set-Based Rare Variant Expression Quantitative Trait Loci in Blood and Brain from Alzheimer Disease Study Participants.

Genes (Basel) 2021 Mar 15;12(3). Epub 2021 Mar 15.

Bioinformatics Graduate Program, Boston University, Boston, MA 02215, USA.

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 and . In the blood, 307 genes were significant targets for rare eSNPs. In the blood and the brain, , , , , and were targets for significant eSNPs. Pathway enrichment analysis revealed significant pathways in the brain ( = 9) and blood ( = 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 (, , , , ) 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.
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http://dx.doi.org/10.3390/genes12030419DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7999141PMC
March 2021

Evaluating Polygenic Risk Scores for Breast Cancer in Women of African Ancestry.

J Natl Cancer Inst 2021 Mar 26. Epub 2021 Mar 26.

Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK.

Background: Polygenic risk scores (PRS) have been demonstrated to identify women of European, Asian and Latino ancestry at elevated risk of developing breast cancer (BC). We evaluated the performance of existing PRSs trained in European ancestry populations among women of African ancestry.

Methods: We assembled genotype data for women of African ancestry, including 9,241 cases and 10,193 controls. We evaluated associations of 179- and 313-variant PRSs with overall and subtype-specific BC risk. PRS discriminatory accuracy was assessed using area under the receiver operating characteristic curve (AUC). We also evaluated a recalibrated PRS, replacing the index variant with variants in each region that better captured risk in women of African ancestry, and estimated lifetime absolute risk of BC in African Americans by PRS category.

Results: For overall BC, the odds ratios per standard deviation of PRS313 was 1.27 (95%CI = 1.23 to 1.31), with an AUC of 0.571 (95%CI = 0.562 to 0.579). Compared to women with average risk (40th-60th PRS percentile), women in the top decile of PRS313 had a 1.54-fold increased risk (95% CI = 1.38 to 1.72). By age 85 years, the absolute risk of overall BC was 19.6% for African American women in the top 1% of PRS313 and 6.7% for those in the lowest 1%. The recalibrated PRS did not improve BC risk prediction.

Conclusion: The PRSs stratify BC risk in women of African ancestry, with attenuated performance compared to that reported in European, Asian and Latina populations. Future work is needed to improve BC risk stratification for women of African ancestry.
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http://dx.doi.org/10.1093/jnci/djab050DOI Listing
March 2021

Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program.

Nature 2021 02 10;590(7845):290-299. Epub 2021 Feb 10.

The Broad Institute of MIT and Harvard, Cambridge, MA, USA.

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). 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%.
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http://dx.doi.org/10.1038/s41586-021-03205-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7875770PMC
February 2021

Identifying factors associated with opioid cessation in a biracial sample using machine learning.

Explor Med 2020 29;1(1):27-41. Epub 2020 Feb 29.

Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA 02118, USA.

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, = 9.19 × 10; EAs: OR = 1.91, = 3.30 × 10), shorter duration of opioid use (AAs: OR = 0.55, = 5.78 × 10; EAs: OR = 0.69, = 3.01 × 10), and older age (AAs: OR = 2.44, = 1.41 × 10; EAs: OR = 2.00, = 5.74 × 10) as the strongest independent predictors of opioid cessation in both AAs and EAs. Attending self-help groups for OUD was also an independent predictor ( < 0.05) in both population groups, while less gambling severity (OR = 0.80, = 3.32 × 10) was specific to AAs and post-traumatic stress disorder recovery (OR = 1.93, = 7.88 × 10), recent antisocial behaviors (OR = 0.64, = 2.69 × 10), and atheism (OR = 1.45, = 1.34 × 10) 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.
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http://dx.doi.org/10.37349/emed.2020.00003DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7861053PMC
February 2020

Genome-wide meta-analysis of muscle weakness identifies 15 susceptibility loci in older men and women.

Nat Commun 2021 01 28;12(1):654. Epub 2021 Jan 28.

Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany.

Low muscle strength is an important heritable indicator of poor health linked to morbidity and mortality in older people. In a genome-wide association study meta-analysis of 256,523 Europeans aged 60 years and over from 22 cohorts we identify 15 loci associated with muscle weakness (European Working Group on Sarcopenia in Older People definition: n = 48,596 cases, 18.9% of total), including 12 loci not implicated in previous analyses of continuous measures of grip strength. Loci include genes reportedly involved in autoimmune disease (HLA-DQA1 p = 4 × 10), arthritis (GDF5 p = 4 × 10), cell cycle control and cancer protection, regulation of transcription, and others involved in the development and maintenance of the musculoskeletal system. Using Mendelian randomization we report possible overlapping causal pathways, including diabetes susceptibility, haematological parameters, and the immune system. We conclude that muscle weakness in older adults has distinct mechanisms from continuous strength, including several pathways considered to be hallmarks of ageing.
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http://dx.doi.org/10.1038/s41467-021-20918-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7844411PMC
January 2021

Novel Alzheimer Disease Risk Loci and Pathways in African American Individuals Using the African Genome Resources Panel: A Meta-analysis.

JAMA Neurol 2021 01;78(1):102-113

Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, New York.

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 gene EDEM1 (3p26; P = 8.9 × 10-7), near the immune response gene ALCAM (3q13; P = 9.3 × 10-7), within GPC6 (13q31; P = 4.1 × 10-7), a gene critical for recruitment of glutamatergic receptors to the neuronal membrane, and within VRK3 (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 near IGF1R at 15q26 (P = 1.7 × 10-9) and 6 additional loci with suggestive significance (P ≤ 5 × 10-7) such as API5 at 11p12 (P = 8.8 × 10-8) and RBFOX1 at 16p13 (P = 5.4 × 10-7) were identified. Gene expression data from brain tissue demonstrate association of ALCAM, ARAP1, GPC6, and RBFOX1 with brain β-amyloid load. Of 25 known loci associated with Alzheimer disease in non-Hispanic White individuals, only APOE, ABCA7, TREM2, BIN1, CD2AP, FERMT2, and WWOX were 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.
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http://dx.doi.org/10.1001/jamaneurol.2020.3536DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7573798PMC
January 2021

Genetic variants in anti-Müllerian hormone-related genes and breast cancer risk: results from the AMBER consortium.

Breast Cancer Res Treat 2021 Jan 22;185(2):469-478. Epub 2020 Sep 22.

Department of Epidemiology, University of North Carolina Gillings School of Global Public Health, 2104F McGavran-Greenberg Hall, Chapel Hill, NC, 27599-7435, USA.

Purpose: Circulating anti-Müllerian hormone (AMH) levels are positively associated with time to menopause and breast cancer risk. We examined breast cancer associations with single nucleotide polymorphisms (SNPs) in the AMH gene or its receptor genes, ACVR1 and AMHR2, among African American women.

Methods: In the AMBER consortium, we tested 65 candidate SNPs, and 1130 total variants, in or near AMH, ACVR1, and AMHR2 and breast cancer risk. Overall, 3649 cases and 4230 controls contributed to analyses. Odds ratios (OR) and 95% confidence intervals (CI) for breast cancer were calculated using multivariable logistic regression.

Results: After correction for multiple comparisons (false-discovery rate of 5%), there were no statistically significant associations with breast cancer risk. Without correction for multiple testing, four candidate SNPs in ACVR1 and one near AMH were associated with breast cancer risk. In ACVR1, rs13395576[C] was associated with lower breast cancer risk overall (OR 0.84; 95% CI 0.72, 0.97) and for ER+ disease (OR 0.75; CI 0.62, 0.89) (p < 0.05). Rs1220110[A] and rs1220134[T] each had ORs of 0.89-0.90 for postmenopausal and ER+ breast cancer (p ≤ 0.03). Conversely, rs1682130[T] was associated with higher risk of ER+ breast cancer (OR 1.17; 95% CI 1.04, 1.32). Near AMH, rs6510652[T] had ORs of 0.85-0.90 for breast cancer overall and after menopause (p ≤ 0.02).

Conclusions: The present results, from a large study of African American women, provide limited support for an association between AMH-related polymorphisms and breast cancer risk and require replication in other studies.
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http://dx.doi.org/10.1007/s10549-020-05944-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7867570PMC
January 2021

Genetic Determinants of Electrocardiographic P-Wave Duration and Relation to Atrial Fibrillation.

Circ Genom Precis Med 2020 10 21;13(5):387-395. Epub 2020 Aug 21.

DZHK (German Center for Cardiovascular Research), partner site Greifswald, Germany (A.T., U.V., M.D., S.B.F.).

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 (, , , , , , , ). The top variants at known sarcomere genes () were associated with longer PWD and increased AF risk. However, top variants at other loci (eg, and ) 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.
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http://dx.doi.org/10.1161/CIRCGEN.119.002874DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7578098PMC
October 2020

Multi-ancestry GWAS of the electrocardiographic PR interval identifies 202 loci underlying cardiac conduction.

Nat Commun 2020 05 21;11(1):2542. Epub 2020 May 21.

Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK.

The electrocardiographic PR interval reflects atrioventricular conduction, and is associated with conduction abnormalities, pacemaker implantation, atrial fibrillation (AF), and cardiovascular mortality. Here we report a multi-ancestry (N = 293,051) genome-wide association meta-analysis for the PR interval, discovering 202 loci of which 141 have not previously been reported. Variants at identified loci increase the percentage of heritability explained, from 33.5% to 62.6%. We observe enrichment for cardiac muscle developmental/contractile and cytoskeletal genes, highlighting key regulation processes for atrioventricular conduction. Additionally, 8 loci not previously reported harbor genes underlying inherited arrhythmic syndromes and/or cardiomyopathies suggesting a role for these genes in cardiovascular pathology in the general population. We show that polygenic predisposition to PR interval duration is an endophenotype for cardiovascular disease, including distal conduction disease, AF, and atrioventricular pre-excitation. These findings advance our understanding of the polygenic basis of cardiac conduction, and the genetic relationship between PR interval duration and cardiovascular disease.
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http://dx.doi.org/10.1038/s41467-020-15706-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7242331PMC
May 2020

Gene discovery for high-density lipoprotein cholesterol level change over time in prospective family studies.

Atherosclerosis 2020 03 14;297:102-110. Epub 2020 Feb 14.

Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St Louis, MO, USA.

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), which encodes a glutamate receptor channel subunit involved in synaptic plasticity. Seven suggestive novel loci (p < 1.0 × 10; 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.
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http://dx.doi.org/10.1016/j.atherosclerosis.2020.02.005DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8098811PMC
March 2020

Exceptionally low likelihood of Alzheimer's dementia in APOE2 homozygotes from a 5,000-person neuropathological study.

Nat Commun 2020 02 3;11(1):667. Epub 2020 Feb 3.

Department of Epidemiology, University of Washington, 1959 NE Pacific Street, Seattle, WA, 98195, USA.

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.
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http://dx.doi.org/10.1038/s41467-019-14279-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6997393PMC
February 2020

Genome-Wide Association Study of Opioid Cessation.

J Clin Med 2020 Jan 9;9(1). Epub 2020 Jan 9.

Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA 02118, USA.

The United States is experiencing an epidemic of opioid use disorder (OUD) and overdose-related deaths. However, the genetic basis for the ability to discontinue opioid use has not been investigated. We performed a genome-wide association study (GWAS) of opioid cessation (defined as abstinence from illicit opioids for >1 year or <6 months before the interview date) in 1130 African American (AA) and 2919 European ancestry (EA) participants recruited for genetic studies of substance use disorders and who met lifetime Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-5) criteria for OUD. Association tests performed separately within each ethnic group were combined by meta-analysis with results obtained from the Comorbidity and Trauma Study. Although there were no genome-wide significant associations, we found suggestive associations with nine independent loci, including three which are biologically relevant: rs4740988 in ( = 2.24 × 10), rs36098404 in ( = 2.24 × 10), and rs592026 in ( = 6.53 × 10). Significant pathways identified in persons of European ancestry (EA) are related to vitamin D metabolism ( = 3.79 × 10) and fibroblast growth factor (FGF) signaling ( = 2.39 × 10). UK Biobank traits including smoking and drinking cessation and chronic back pain were significantly associated with opioid cessation using GWAS-derived polygenic risk scores. These results provide evidence for genetic influences on opioid cessation, suggest genetic overlap with other relevant traits, and may indicate potential novel therapeutic targets for OUD.
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http://dx.doi.org/10.3390/jcm9010180DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7019731PMC
January 2020

Integrative Omics Approach to Identifying Genes Associated With Atrial Fibrillation.

Circ Res 2020 01 5;126(3):350-360. Epub 2019 Dec 5.

Boston University and National Heart, Lung and Blood Institute's Framingham Heart Study, Framingham, MA (K.L.L., J.D., L.T., E.J.B., H.L.).

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. To develop an approach to identify additional AF-related genes by integrating multiple omics data. 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%). 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.
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http://dx.doi.org/10.1161/CIRCRESAHA.119.315179DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7004281PMC
January 2020

Monogenic and Polygenic Contributions to Atrial Fibrillation Risk: Results From a National Biobank.

Circ Res 2020 01 6;126(2):200-209. Epub 2019 Nov 6.

From the Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA (S.H.C., S.J.J., L.-C.W., J.P.P., C.R., M.C., C.J.-Y.L., A.W.H., A.V.K., S.A.L., P.T.E.).

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 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, (odds ratio, 2.71, =2.50×10). The association with AF was more significant (odds ratio, 6.15, =3.26×10) when restricting to LOF variants located in exons highly expressed in cardiac tissue (). Overall, 0.44% of individuals carried 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 variants only accounted for 0.2%.

Conclusions: Both monogenic and polygenic factors contribute to AF risk in the general population. While rare variants confer a substantial AF penetrance, the additive effect of many common variants explains a larger proportion of genetic susceptibility to AF.
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http://dx.doi.org/10.1161/CIRCRESAHA.119.315686DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7007701PMC
January 2020

Comparison of On-Site Versus Remote Mobile Device Support in the Framingham Heart Study Using the Health eHeart Study for Digital Follow-up: Randomized Pilot Study Set Within an Observational Study Design.

JMIR Mhealth Uhealth 2019 09 30;7(9):e13238. Epub 2019 Sep 30.

Framingham Heart Study, Framingham, MA, United States.

Background: New electronic cohort (e-Cohort) study designs provide resource-effective methods for collecting participant data. It is unclear if implementing an e-Cohort study without direct, in-person participant contact can achieve successful participation rates.

Objective: The objective of this study was to compare 2 distinct enrollment methods for setting up mobile health (mHealth) devices and to assess the ongoing adherence to device use in an e-Cohort pilot study.

Methods: We coenrolled participants from the Framingham Heart Study (FHS) into the FHS-Health eHeart (HeH) pilot study, a digital cohort with infrastructure for collecting mHealth data. FHS participants who had an email address and smartphone were randomized to our FHS-HeH pilot study into 1 of 2 study arms: remote versus on-site support. We oversampled older adults (age ≥65 years), with a target of enrolling 20% of our sample as older adults. In the remote arm, participants received an email containing a link to enrollment website and, upon enrollment, were sent 4 smartphone-connectable sensor devices. Participants in the on-site arm were invited to visit an in-person FHS facility and were provided in-person support for enrollment and connecting the devices. Device data were tracked for at least 5 months.

Results: Compared with the individuals who declined, individuals who consented to our pilot study (on-site, n=101; remote, n=93) were more likely to be women, highly educated, and younger. In the on-site arm, the connection and initial use of devices was ≥20% higher than the remote arm (mean percent difference was 25% [95% CI 17-35] for activity monitor, 22% [95% CI 12-32] for blood pressure cuff, 20% [95% CI 10-30] for scale, and 43% [95% CI 30-55] for electrocardiogram), with device connection rates in the on-site arm of 99%, 95%, 95%, and 84%. Once connected, continued device use over the 5-month study period was similar between the study arms.

Conclusions: Our pilot study demonstrated that the deployment of mobile devices among middle-aged and older adults in the context of an on-site clinic visit was associated with higher initial rates of device use as compared with offering only remote support. Once connected, the device use was similar in both groups.
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http://dx.doi.org/10.2196/13238DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6792023PMC
September 2019

Promoter Polymorphism-219T/G is an Effect Modifier of the Influence of ε4 on Alzheimer's Disease Risk in a Multiracial Sample.

J Clin Med 2019 Aug 16;8(8). Epub 2019 Aug 16.

Department of Molecular Genetics, Brain Research Institute, Niigata University, Niigata 951-8585, Japan.

Variants in the gene region may explain ethnic differences in the association of Alzheimer's disease (AD) with ε4. Ethnic differences in allele frequencies for three region SNPs (single nucleotide polymorphisms) were identified and tested for association in 19,398 East Asians (EastA), including Koreans and Japanese, 15,836 European ancestry (EuroA) individuals, and 4985 African Americans, and with brain imaging measures of cortical atrophy in sub-samples of Koreans and EuroAs. Among ε4/ε4 individuals, AD risk increased substantially in a dose-dependent manner with the number of promoter SNP rs405509 alleles in EastAs : OR (odds ratio) = 27.02, = 8.80 × 10; : OR = 15.87, = 2.62 × 10) and EuroAs (: OR = 18.13, = 2.69 × 10; : OR = 12.63, = 3.44 × 10), and rs405509- homozygotes had a younger onset and more severe cortical atrophy than those with -allele. Functional experiments using promoter fragments demonstrated that lowered expression in human brain and serum. The modifying effect of rs405509 genotype explained much of the ethnic variability in the AD/ε4 association, and increasing expression might lower AD risk among ε4 homozygotes.
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http://dx.doi.org/10.3390/jcm8081236DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6723529PMC
August 2019

A meta-analysis of genome-wide association studies identifies multiple longevity genes.

Nat Commun 2019 08 14;10(1):3669. Epub 2019 Aug 14.

Department of Public Health, University of Southern Denmark, 5000, Odense C, Denmark.

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.
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http://dx.doi.org/10.1038/s41467-019-11558-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6694136PMC
August 2019

Refining the Association Between Body Mass Index and Atrial Fibrillation: G-Formula and Restricted Mean Survival Times.

J Am Heart Assoc 2019 08 8;8(16):e013011. Epub 2019 Aug 8.

Department of Biostatistics Boston University School of Public Health Boston MA.

Background Previous studies assessing the association between body mass index (BMI) and atrial fibrillation (AF) did not account for time-varying covariates, which may be affected by previous BMI. We illustrate how the g-formula can account for time-varying confounding. Methods and Results We included 4392 participants from the Framingham Heart Study who were AF free at ages 45 to 55 years, and followed them for up to 20 years. We estimated hazard ratios (HRs) comparing time-varying nonobese versus obese with Cox models. We used the g-formula to compare nonobese versus obese and 10% annual decrease in BMI (until normal weight is reached) versus natural course. We estimated HRs and differences in restricted mean survival times, the mean difference in time alive and AF free. We adjusted for sex, age, and time-varying risk factors. Cox models indicated that nonobese participants had a decreased rate of AF versus obese participants (HR, 0.83; 95% CI, 0.72-0.97). G-formula analyses comparing everyone had they been nonobese versus obese yielded stronger associations (HR, 0.73; 95% CI, 0.58-0.91). The restricted mean survival time was 19.22 years had everyone been nonobese and 19.03 years had everyone been obese (difference, 2.25 months; 95% CI, -0.66 to 5.16). When assessing a 10% annual decrease in BMI, the association was weaker (HR 0.96; 95% CI, 0.86-1.08). Conclusions Decreased BMI was associated with a lower rate of AF after accounting for time-varying covariates that depend on previous exposure using the g-formula, which Cox models cannot accommodate. Absolute measures like the restricted mean survival time difference offer context to relative measures of association.
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http://dx.doi.org/10.1161/JAHA.119.013011DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6759878PMC
August 2019

Correction for multiple testing in candidate-gene methylation studies.

Epigenomics 2019 07 26;11(9):1089-1105. Epub 2019 Jun 26.

National Center for PTSD, VA Boston Healthcare System, Boston, MA 02130, USA.

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 (GEA), and Li and Ji methods. The experiment-wide type 1 error rate was examined in simulations based on Illumina EPIC and 450K data. 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. For genes with substantial correlation across measured CpGs, GEA and ETT can appropriately correct for multiple testing in candidate gene methylation studies.
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http://dx.doi.org/10.2217/epi-2018-0204DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7132638PMC
July 2019

Genetic associations with age of menopause in familial longevity.

Menopause 2019 10;26(10):1204-1212

Department of Biostatistics, Boston University School of Public Health, Boston, MA.

Objective: 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.

Methods: 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.

Results: 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 reached >10 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.

Conclusions: 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.

Video Summary: Supplemental Digital Content 1, http://links.lww.com/MENO/A420.
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http://dx.doi.org/10.1097/GME.0000000000001367DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7008937PMC
October 2019

Healthy diet is associated with gene expression in blood: the Framingham Heart Study.

Am J Clin Nutr 2019 09;110(3):742-749

National Heart, Lung, and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA.

Background: Genes in metabolic and nutrient signaling pathways play important roles in lifespan in model organisms and human longevity.

Objective: The aim of this study was to examine the relation of a quantitative measure of healthy diet to gene expression in a community-based cohort.

Methods: We used the 2015 Dietary Guidelines for Americans Adherence Index (DGAI) score to quantify key dietary recommendations of an overall healthy diet. Our current analyses included 2220 Offspring participants (mean age 66 ± 9 y, 55.4% women) and 2941 Third-Generation participants (mean age 46 ± 9 y, 54.5% women) from the Framingham Heart Study. Gene expression was profiled in blood through the use of the Affymetrix Human Exon 1.0 ST Array. We conducted a transcriptome-wide association study of DGAI adjusting for age, sex, smoking, cell counts, and technical covariates. We also constructed a combined gene score from genes significantly associated with DGAI.

Results: The DGAI was significantly associated with the expression of 19 genes (false discovery rate <0.05). The most significant gene, ARRDC3, is a member of the arrestin family of proteins, and evidence in animal models and human data suggests that this gene is a regulator of obesity and energy expenditure. The DGAI gene score was associated with body mass index (P = 1.4 × 10-50), fasting glucose concentration (P = 2.5 × 10-11), type 2 diabetes (P = 1.1 × 10-5), and metabolic syndrome (P = 1.8 × 10-32).

Conclusions: Healthier diet was associated with genes involved in metabolic function. Further work is needed to replicate our findings and investigate the relation of a healthy diet to altered gene regulation.
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http://dx.doi.org/10.1093/ajcn/nqz060DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6736078PMC
September 2019

Analysis of Whole-Exome Sequencing Data for Alzheimer Disease Stratified by APOE Genotype.

JAMA Neurol 2019 Sep;76(9):1099-1108

Department of Medicine (Biomedical Genetics), Boston University Schools of Medicine and Public Health, Boston, Massachusetts.

Importance: Previous genome-wide association studies of common variants identified associations for Alzheimer disease (AD) loci evident only among individuals with particular APOE alleles.

Objective: To identify APOE genotype-dependent associations with infrequent and rare variants using whole-exome sequencing.

Design, Setting, And Participants: The discovery stage included 10 441 non-Hispanic white participants in the Alzheimer Disease Sequencing Project. Replication was sought in 2 independent, whole-exome sequencing data sets (1766 patients with AD, 2906 without AD [controls]) and a chip-based genotype imputation data set (8728 patients with AD, 9808 controls). Bioinformatics and functional analyses were conducted using clinical, cognitive, neuropathologic, whole-exome sequencing, and gene expression data obtained from a longitudinal cohort sample including 402 patients with AD and 647 controls. Data were analyzed between March 2017 and September 2018.

Main Outcomes And Measures: Score, Firth, and sequence kernel association tests were used to test the association of AD risk with individual variants and genes in subgroups of APOE ε4 carriers and noncarriers. Results with P ≤ 1 × 10-5 were further evaluated in the replication data sets and combined by meta-analysis.

Results: Among 3145 patients with AD and 4213 controls lacking ε4 (mean [SD] age, 83.4 [7.6] years; 4363 [59.3.%] women), novel genome-wide significant associations were obtained in the discovery sample with rs536940594 in AC099552 (odds ratio [OR], 88.0; 95% CI, 9.08-852.0; P = 2.22 × 10-7) and rs138412600 in GPAA1 (OR, 1.78; 95% CI, 1.44-2.2; meta-P = 7.81 × 10-8). GPAA1 was also associated with expression in the brain of GPAA1 (β = -0.08; P = .03) and its repressive transcription factor, FOXG1 (β = 0.13; P = .003), and global cognition function (β = -0.53; P = .009). Significant gene-wide associations (threshold P ≤ 6.35 × 10-7) were observed for OR8G5 (P = 4.67 × 10-7), IGHV3-7 (P = 9.75 × 10-16), and SLC24A3 (P = 2.67 × 10-12) in 2377 patients with AD and 706 controls with ε4 (mean [SD] age, 75.2 [9.6] years; 1668 [54.1%] women).

Conclusions And Relevance: The study identified multiple possible novel associations for AD with individual and aggregated rare variants in groups of individuals with and without APOE ε4 alleles that reinforce known and suggest additional pathways leading to AD.
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http://dx.doi.org/10.1001/jamaneurol.2019.1456DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6563544PMC
September 2019

CpG-related SNPs in the MS4A region have a dose-dependent effect on risk of late-onset Alzheimer disease.

Aging Cell 2019 08 29;18(4):e12964. Epub 2019 May 29.

Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts.

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 < 5 × 10 ) associations were identified with 171 1.0 kb-length windows spanning 932 kb in the APOE region (top p < 2.2 × 10 ), five windows at BIN1 (top p = 1.3 × 10 ), two windows at MS4A6A (top p = 2.7 × 10 ), two windows near MS4A4A (top p = 6.4 × 10 ), and one window at PICALM (p = 6.3 × 10 ). The total number of CGS-derived CpG dinucleotides in the window near MS4A4A was associated with AD risk (p = 2.67 × 10 ), brain DNA methylation (p = 2.15 × 10 ), and gene expression in brain (p = 0.03) and blood (p = 2.53 × 10 ). Pathway analysis of the genes responsive to changes in the methylation quantitative trait locus signal at MS4A4A (cg14750746) showed an enrichment of methyltransferase functions. We confirm the importance of CGS in AD and the potential for creating a functional CpG dosage-derived genetic score to predict AD risk.
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http://dx.doi.org/10.1111/acel.12964DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6612647PMC
August 2019

Maternal and fetal genetic effects on birth weight and their relevance to cardio-metabolic risk factors.

Nat Genet 2019 05 1;51(5):804-814. Epub 2019 May 1.

Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK.

Birth weight variation is influenced by fetal and maternal genetic and non-genetic factors, and has been reproducibly associated with future cardio-metabolic health outcomes. In expanded genome-wide association analyses of own birth weight (n = 321,223) and offspring birth weight (n = 230,069 mothers), we identified 190 independent association signals (129 of which are novel). We used structural equation modeling to decompose the contributions of direct fetal and indirect maternal genetic effects, then applied Mendelian randomization to illuminate causal pathways. For example, both indirect maternal and direct fetal genetic effects drive the observational relationship between lower birth weight and higher later blood pressure: maternal blood pressure-raising alleles reduce offspring birth weight, but only direct fetal effects of these alleles, once inherited, increase later offspring blood pressure. Using maternal birth weight-lowering genotypes to proxy for an adverse intrauterine environment provided no evidence that it causally raises offspring blood pressure, indicating that the inverse birth weight-blood pressure association is attributable to genetic effects, and not to intrauterine programming.
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http://dx.doi.org/10.1038/s41588-019-0403-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6522365PMC
May 2019

Association of Rare Coding Mutations With Alzheimer Disease and Other Dementias Among Adults of European Ancestry.

JAMA Netw Open 2019 03 1;2(3):e191350. Epub 2019 Mar 1.

Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, Massachusetts.

Importance: Some of the unexplained heritability of Alzheimer disease (AD) may be due to rare variants whose effects are not captured in genome-wide association studies because very large samples are needed to observe statistically significant associations.

Objective: To identify genetic variants associated with AD risk using a nonstatistical approach.

Design, Setting, And Participants: Genetic association study in which rare variants were identified by whole-exome sequencing in unrelated individuals of European ancestry from the Alzheimer's Disease Sequencing Project (ADSP). Data were analyzed between March 2017 and September 2018.

Main Outcomes And Measures: Minor alleles genome-wide and in 95 genes previously associated with AD, AD-related traits, or other dementias were tabulated and filtered for predicted functional impact and occurrence in participants with AD but not controls. Support for several findings was sought in a whole-exome sequencing data set comprising 19 affected relative pairs from Utah high-risk pedigrees and whole-genome sequencing data sets from the ADSP and Alzheimer's Disease Neuroimaging Initiative.

Results: Among 5617 participants with AD (3202 [57.0%] women; mean [SD] age, 76.4 [9.3] years) and 4594 controls (2719 [59.0%] women; mean [SD] age, 86.5 [4.5] years), a total of 24 variants with moderate or high functional impact from 19 genes were observed in 10 or more participants with AD but not in controls. These variants included a missense mutation (rs149307620 [p.A284T], n = 10) in NOTCH3, a gene in which coding mutations are associated with cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), that was also identified in 1 participant with AD and 1 participant with mild cognitive impairment in the whole genome sequencing data sets. Four participants with AD carried the TREM2 rs104894002 (p.Q33X) high-impact mutation that, in homozygous form, causes Nasu-Hakola disease, a rare disorder characterized by early-onset dementia and multifocal bone cysts, suggesting an intermediate inheritance model for the mutation. Compared with controls, participants with AD had a significantly higher burden of deleterious rare coding variants in dementia-associated genes (2314 vs 3354 cumulative variants, respectively; P = .006).

Conclusions And Relevance: Different mutations in the same gene or variable dose of a mutation may be associated with result in distinct dementias. These findings suggest that minor differences in the structure or amount of protein may be associated with in different clinical outcomes. Understanding these genotype-phenotype associations may provide further insight into the pathogenic nature of the mutations, as well as offer clues for developing new therapeutic targets.
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http://dx.doi.org/10.1001/jamanetworkopen.2019.1350DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6450321PMC
March 2019

Genetic meta-analysis of diagnosed Alzheimer's disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing.

Nat Genet 2019 03 28;51(3):414-430. Epub 2019 Feb 28.

Research Center and Memory Clinic of Fundació ACE, Institut Català de Neurociències Aplicades-Universitat Internacional de Catalunya, Barcelona, Spain.

Risk for late-onset Alzheimer's disease (LOAD), the most prevalent dementia, is partially driven by genetics. To identify LOAD risk loci, we performed a large genome-wide association meta-analysis of clinically diagnosed LOAD (94,437 individuals). We confirm 20 previous LOAD risk loci and identify five new genome-wide loci (IQCK, ACE, ADAM10, ADAMTS1, and WWOX), two of which (ADAM10, ACE) were identified in a recent genome-wide association (GWAS)-by-familial-proxy of Alzheimer's or dementia. Fine-mapping of the human leukocyte antigen (HLA) region confirms the neurological and immune-mediated disease haplotype HLA-DR15 as a risk factor for LOAD. Pathway analysis implicates immunity, lipid metabolism, tau binding proteins, and amyloid precursor protein (APP) metabolism, showing that genetic variants affecting APP and Aβ processing are associated not only with early-onset autosomal dominant Alzheimer's disease but also with LOAD. Analyses of risk genes and pathways show enrichment for rare variants (P = 1.32 × 10), indicating that additional rare variants remain to be identified. We also identify important genetic correlations between LOAD and traits such as family history of dementia and education.
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http://dx.doi.org/10.1038/s41588-019-0358-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6463297PMC
March 2019