Genome‐wide Interaction and Stratified Study with Smoking Identifies Association of APAF1 and MIXL1/LIN9 with Alzheimer’s Disease
Background Alzheimer’s disease (AD) has both genetic and environmental risk factors. Gene‐environment interaction may help explain some missing heritability. There is strong evidence for cigarette smoking as a risk factor for AD. To identify genetic‐smoking‐related associations with AD, we conducted...
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| creator | Dacey, Ryan Han, Xudong Moore, Mackenzie R Chung, Jaeyoon Durape, Shruti Rosenthaler, Max Uretsky, Madeline Abdolmohammadi, Bobak Lee, Annie J. Brickman, Adam M. Hohman, Timothy J. Cuccaro, Michael L. Bennett, David A. Crane, Paul K. Kamboh, M. Ilyas Kukull, Walter A. Au, Rhoda Haines, Jonathan L. Pericak‐Vance, Margaret A. Schellenberg, Gerard D. Mayeux, Richard Lunetta, Kathryn L. Farrer, Lindsay A. Mez, Jesse |
| description | Background
Alzheimer’s disease (AD) has both genetic and environmental risk factors. Gene‐environment interaction may help explain some missing heritability. There is strong evidence for cigarette smoking as a risk factor for AD. To identify genetic‐smoking‐related associations with AD, we conducted a genome‐wide association study (GWAS) assessing a SNP‐smoking interaction and stratified analysis by smoking status.
Method
Lifetime smoking data were available and analyzed among 22,030 non‐Hispanic White (NHW; 8,232 cases; 13,798 controls) and 3,126 African American (AFA; 921 cases; 2,205 controls) participants from the AD Genetic Consortium and the Framingham Heart Study. “Ever smoking” status was considered as a dichotomous exposure, defined by current smoking status or past history of smoking. Across 35 datasets, we conducted GWAS with two approaches: inclusion of a SNP‐by‐smoking interaction term and stratification by smoking status (12,080 smokers, 13,428 non‐smokers). MAGEE was used to estimate SNP‐by‐smoking interaction effects and SAIGE was used to estimate SNP effects in stratified analysis. Age, sex, and principal components for population structure were included as covariates. METAL was used for inverse‐variance weighted meta‐analysis across datasets to estimate within‐ and cross‐ancestry effects.
Result
The stratified analysis identified a genome‐wide significant association among smokers in APAF1 on chromosome 12 (top SNP: rs12368451; smokers: MAF = 0.44, p = 2.2 × 10‐8, OR = 1.20; non‐smokers: MAF = 0.44, p = 0.97, OR = 1.00). Effects were present in both ancestry groups (NHW: MAF = 0.45, p = 6.1 × 10‐6, OR = 1.16; AFA: MAF = 0.35, p = 6.6 × 10‐5, OR = 1.46). APAF1 has been linked to gene‐smoking interaction for non‐AD related outcomes. A neighboring gene, ANKS1B, is highly expressed in the brain, interacts with amyloid‐b precursor protein, and has shown GWAS signals for smoking initiation and cognitive ability. We also identified a genome‐wide significant SNP‐by‐smoking interaction in the MIXL1/LIN9 region on chromosome 1 (top SNP: rs1091961, MAF = 0.35, p = 4.9 × 10‐8, βSNP*smoking = 0.24; smokers: OR = 1.12, p = 0.0006; non‐smokers: OR = 0.89, p = 0.0001). Within LIN9, several SNPs in linkage disequilibrium with rs1091961 have shown sub‐genome wide association with nicotine dependence.
Conclusion
In this gene‐smoking interaction and smoking‐stratified GWAS of AD, we identified two promising loci. These findings highlight the strength of util |
| doi_str_mv | 10.1002/alz.091434 |
| format | Article |
| fullrecord | <record><control><sourceid>wiley_cross</sourceid><recordid>TN_cdi_crossref_primary_10_1002_alz_091434</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>ALZ091434</sourcerecordid><originalsourceid>FETCH-LOGICAL-c774-e7ea1c7c1fa6ca166535a4a161cc94af72e62d3cbacd04cf169e901fdece73193</originalsourceid><addsrcrecordid>eNp9kLtOwzAUhi0EEqWw8ASekdL65GYyRgVKpHCR2gGxRMY-poZckB1UtVMXdlZer09C21SMTOeXzv_9w0fIObABMOYPRbkcsATCIDwgPYgi34t8nhz-5ZgdkxPn3hgL2SVEPfI1xrqpcL36nhuFNKtbtEK2pqmpqBWdtFa0Rhvcxk-1oHPTzuikat5N_UozhfXu62jqXCON2IGNpuljegO7hbvsKYdhnt0nHZuWyxmaCu169ePolXEoHJ6SIy1Kh2f72yfTm-vp6NbLH8bZKM09yXnoIUcBkkvQIpYC4jgKIhFuAkiZhEJzH2NfBfJFSMVCqSFOMGGgFUrkASRBn1x0s9I2zlnUxYc1lbCLAlix9Vds_BWdv00ZuvLclLj4p1mk-fOe-QW66HX2</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Genome‐wide Interaction and Stratified Study with Smoking Identifies Association of APAF1 and MIXL1/LIN9 with Alzheimer’s Disease</title><source>PubMed Central Open Access</source><source>Wiley Online Library Open Access</source><source>Wiley Online Library All Journals</source><source>PubMed Central</source><creator>Dacey, Ryan ; Han, Xudong ; Moore, Mackenzie R ; Chung, Jaeyoon ; Durape, Shruti ; Rosenthaler, Max ; Uretsky, Madeline ; Abdolmohammadi, Bobak ; Lee, Annie J. ; Brickman, Adam M. ; Hohman, Timothy J. ; Cuccaro, Michael L. ; Bennett, David A. ; Crane, Paul K. ; Kamboh, M. Ilyas ; Kukull, Walter A. ; Au, Rhoda ; Haines, Jonathan L. ; Pericak‐Vance, Margaret A. ; Schellenberg, Gerard D. ; Mayeux, Richard ; Lunetta, Kathryn L. ; Farrer, Lindsay A. ; Mez, Jesse</creator><creatorcontrib>Dacey, Ryan ; Han, Xudong ; Moore, Mackenzie R ; Chung, Jaeyoon ; Durape, Shruti ; Rosenthaler, Max ; Uretsky, Madeline ; Abdolmohammadi, Bobak ; Lee, Annie J. ; Brickman, Adam M. ; Hohman, Timothy J. ; Cuccaro, Michael L. ; Bennett, David A. ; Crane, Paul K. ; Kamboh, M. Ilyas ; Kukull, Walter A. ; Au, Rhoda ; Haines, Jonathan L. ; Pericak‐Vance, Margaret A. ; Schellenberg, Gerard D. ; Mayeux, Richard ; Lunetta, Kathryn L. ; Farrer, Lindsay A. ; Mez, Jesse</creatorcontrib><description>Background
Alzheimer’s disease (AD) has both genetic and environmental risk factors. Gene‐environment interaction may help explain some missing heritability. There is strong evidence for cigarette smoking as a risk factor for AD. To identify genetic‐smoking‐related associations with AD, we conducted a genome‐wide association study (GWAS) assessing a SNP‐smoking interaction and stratified analysis by smoking status.
Method
Lifetime smoking data were available and analyzed among 22,030 non‐Hispanic White (NHW; 8,232 cases; 13,798 controls) and 3,126 African American (AFA; 921 cases; 2,205 controls) participants from the AD Genetic Consortium and the Framingham Heart Study. “Ever smoking” status was considered as a dichotomous exposure, defined by current smoking status or past history of smoking. Across 35 datasets, we conducted GWAS with two approaches: inclusion of a SNP‐by‐smoking interaction term and stratification by smoking status (12,080 smokers, 13,428 non‐smokers). MAGEE was used to estimate SNP‐by‐smoking interaction effects and SAIGE was used to estimate SNP effects in stratified analysis. Age, sex, and principal components for population structure were included as covariates. METAL was used for inverse‐variance weighted meta‐analysis across datasets to estimate within‐ and cross‐ancestry effects.
Result
The stratified analysis identified a genome‐wide significant association among smokers in APAF1 on chromosome 12 (top SNP: rs12368451; smokers: MAF = 0.44, p = 2.2 × 10‐8, OR = 1.20; non‐smokers: MAF = 0.44, p = 0.97, OR = 1.00). Effects were present in both ancestry groups (NHW: MAF = 0.45, p = 6.1 × 10‐6, OR = 1.16; AFA: MAF = 0.35, p = 6.6 × 10‐5, OR = 1.46). APAF1 has been linked to gene‐smoking interaction for non‐AD related outcomes. A neighboring gene, ANKS1B, is highly expressed in the brain, interacts with amyloid‐b precursor protein, and has shown GWAS signals for smoking initiation and cognitive ability. We also identified a genome‐wide significant SNP‐by‐smoking interaction in the MIXL1/LIN9 region on chromosome 1 (top SNP: rs1091961, MAF = 0.35, p = 4.9 × 10‐8, βSNP*smoking = 0.24; smokers: OR = 1.12, p = 0.0006; non‐smokers: OR = 0.89, p = 0.0001). Within LIN9, several SNPs in linkage disequilibrium with rs1091961 have shown sub‐genome wide association with nicotine dependence.
Conclusion
In this gene‐smoking interaction and smoking‐stratified GWAS of AD, we identified two promising loci. These findings highlight the strength of utilizing cross‐ancestry datasets and considering both genetic and environmental factors together towards a personalized medicine approach to AD.</description><identifier>ISSN: 1552-5260</identifier><identifier>EISSN: 1552-5279</identifier><identifier>DOI: 10.1002/alz.091434</identifier><language>eng</language><ispartof>Alzheimer's & dementia, 2024-12, Vol.20 (S1), p.n/a</ispartof><rights>2024 The Alzheimer's Association. published by Wiley Periodicals LLC on behalf of Alzheimer's Association.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Falz.091434$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Falz.091434$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,1416,11561,27923,27924,45573,45574,46051,46475</link.rule.ids></links><search><creatorcontrib>Dacey, Ryan</creatorcontrib><creatorcontrib>Han, Xudong</creatorcontrib><creatorcontrib>Moore, Mackenzie R</creatorcontrib><creatorcontrib>Chung, Jaeyoon</creatorcontrib><creatorcontrib>Durape, Shruti</creatorcontrib><creatorcontrib>Rosenthaler, Max</creatorcontrib><creatorcontrib>Uretsky, Madeline</creatorcontrib><creatorcontrib>Abdolmohammadi, Bobak</creatorcontrib><creatorcontrib>Lee, Annie J.</creatorcontrib><creatorcontrib>Brickman, Adam M.</creatorcontrib><creatorcontrib>Hohman, Timothy J.</creatorcontrib><creatorcontrib>Cuccaro, Michael L.</creatorcontrib><creatorcontrib>Bennett, David A.</creatorcontrib><creatorcontrib>Crane, Paul K.</creatorcontrib><creatorcontrib>Kamboh, M. Ilyas</creatorcontrib><creatorcontrib>Kukull, Walter A.</creatorcontrib><creatorcontrib>Au, Rhoda</creatorcontrib><creatorcontrib>Haines, Jonathan L.</creatorcontrib><creatorcontrib>Pericak‐Vance, Margaret A.</creatorcontrib><creatorcontrib>Schellenberg, Gerard D.</creatorcontrib><creatorcontrib>Mayeux, Richard</creatorcontrib><creatorcontrib>Lunetta, Kathryn L.</creatorcontrib><creatorcontrib>Farrer, Lindsay A.</creatorcontrib><creatorcontrib>Mez, Jesse</creatorcontrib><title>Genome‐wide Interaction and Stratified Study with Smoking Identifies Association of APAF1 and MIXL1/LIN9 with Alzheimer’s Disease</title><title>Alzheimer's & dementia</title><description>Background
Alzheimer’s disease (AD) has both genetic and environmental risk factors. Gene‐environment interaction may help explain some missing heritability. There is strong evidence for cigarette smoking as a risk factor for AD. To identify genetic‐smoking‐related associations with AD, we conducted a genome‐wide association study (GWAS) assessing a SNP‐smoking interaction and stratified analysis by smoking status.
Method
Lifetime smoking data were available and analyzed among 22,030 non‐Hispanic White (NHW; 8,232 cases; 13,798 controls) and 3,126 African American (AFA; 921 cases; 2,205 controls) participants from the AD Genetic Consortium and the Framingham Heart Study. “Ever smoking” status was considered as a dichotomous exposure, defined by current smoking status or past history of smoking. Across 35 datasets, we conducted GWAS with two approaches: inclusion of a SNP‐by‐smoking interaction term and stratification by smoking status (12,080 smokers, 13,428 non‐smokers). MAGEE was used to estimate SNP‐by‐smoking interaction effects and SAIGE was used to estimate SNP effects in stratified analysis. Age, sex, and principal components for population structure were included as covariates. METAL was used for inverse‐variance weighted meta‐analysis across datasets to estimate within‐ and cross‐ancestry effects.
Result
The stratified analysis identified a genome‐wide significant association among smokers in APAF1 on chromosome 12 (top SNP: rs12368451; smokers: MAF = 0.44, p = 2.2 × 10‐8, OR = 1.20; non‐smokers: MAF = 0.44, p = 0.97, OR = 1.00). Effects were present in both ancestry groups (NHW: MAF = 0.45, p = 6.1 × 10‐6, OR = 1.16; AFA: MAF = 0.35, p = 6.6 × 10‐5, OR = 1.46). APAF1 has been linked to gene‐smoking interaction for non‐AD related outcomes. A neighboring gene, ANKS1B, is highly expressed in the brain, interacts with amyloid‐b precursor protein, and has shown GWAS signals for smoking initiation and cognitive ability. We also identified a genome‐wide significant SNP‐by‐smoking interaction in the MIXL1/LIN9 region on chromosome 1 (top SNP: rs1091961, MAF = 0.35, p = 4.9 × 10‐8, βSNP*smoking = 0.24; smokers: OR = 1.12, p = 0.0006; non‐smokers: OR = 0.89, p = 0.0001). Within LIN9, several SNPs in linkage disequilibrium with rs1091961 have shown sub‐genome wide association with nicotine dependence.
Conclusion
In this gene‐smoking interaction and smoking‐stratified GWAS of AD, we identified two promising loci. These findings highlight the strength of utilizing cross‐ancestry datasets and considering both genetic and environmental factors together towards a personalized medicine approach to AD.</description><issn>1552-5260</issn><issn>1552-5279</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>WIN</sourceid><recordid>eNp9kLtOwzAUhi0EEqWw8ASekdL65GYyRgVKpHCR2gGxRMY-poZckB1UtVMXdlZer09C21SMTOeXzv_9w0fIObABMOYPRbkcsATCIDwgPYgi34t8nhz-5ZgdkxPn3hgL2SVEPfI1xrqpcL36nhuFNKtbtEK2pqmpqBWdtFa0Rhvcxk-1oHPTzuikat5N_UozhfXu62jqXCON2IGNpuljegO7hbvsKYdhnt0nHZuWyxmaCu169ePolXEoHJ6SIy1Kh2f72yfTm-vp6NbLH8bZKM09yXnoIUcBkkvQIpYC4jgKIhFuAkiZhEJzH2NfBfJFSMVCqSFOMGGgFUrkASRBn1x0s9I2zlnUxYc1lbCLAlix9Vds_BWdv00ZuvLclLj4p1mk-fOe-QW66HX2</recordid><startdate>202412</startdate><enddate>202412</enddate><creator>Dacey, Ryan</creator><creator>Han, Xudong</creator><creator>Moore, Mackenzie R</creator><creator>Chung, Jaeyoon</creator><creator>Durape, Shruti</creator><creator>Rosenthaler, Max</creator><creator>Uretsky, Madeline</creator><creator>Abdolmohammadi, Bobak</creator><creator>Lee, Annie J.</creator><creator>Brickman, Adam M.</creator><creator>Hohman, Timothy J.</creator><creator>Cuccaro, Michael L.</creator><creator>Bennett, David A.</creator><creator>Crane, Paul K.</creator><creator>Kamboh, M. Ilyas</creator><creator>Kukull, Walter A.</creator><creator>Au, Rhoda</creator><creator>Haines, Jonathan L.</creator><creator>Pericak‐Vance, Margaret A.</creator><creator>Schellenberg, Gerard D.</creator><creator>Mayeux, Richard</creator><creator>Lunetta, Kathryn L.</creator><creator>Farrer, Lindsay A.</creator><creator>Mez, Jesse</creator><scope>24P</scope><scope>WIN</scope><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>202412</creationdate><title>Genome‐wide Interaction and Stratified Study with Smoking Identifies Association of APAF1 and MIXL1/LIN9 with Alzheimer’s Disease</title><author>Dacey, Ryan ; Han, Xudong ; Moore, Mackenzie R ; Chung, Jaeyoon ; Durape, Shruti ; Rosenthaler, Max ; Uretsky, Madeline ; Abdolmohammadi, Bobak ; Lee, Annie J. ; Brickman, Adam M. ; Hohman, Timothy J. ; Cuccaro, Michael L. ; Bennett, David A. ; Crane, Paul K. ; Kamboh, M. Ilyas ; Kukull, Walter A. ; Au, Rhoda ; Haines, Jonathan L. ; Pericak‐Vance, Margaret A. ; Schellenberg, Gerard D. ; Mayeux, Richard ; Lunetta, Kathryn L. ; Farrer, Lindsay A. ; Mez, Jesse</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c774-e7ea1c7c1fa6ca166535a4a161cc94af72e62d3cbacd04cf169e901fdece73193</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Dacey, Ryan</creatorcontrib><creatorcontrib>Han, Xudong</creatorcontrib><creatorcontrib>Moore, Mackenzie R</creatorcontrib><creatorcontrib>Chung, Jaeyoon</creatorcontrib><creatorcontrib>Durape, Shruti</creatorcontrib><creatorcontrib>Rosenthaler, Max</creatorcontrib><creatorcontrib>Uretsky, Madeline</creatorcontrib><creatorcontrib>Abdolmohammadi, Bobak</creatorcontrib><creatorcontrib>Lee, Annie J.</creatorcontrib><creatorcontrib>Brickman, Adam M.</creatorcontrib><creatorcontrib>Hohman, Timothy J.</creatorcontrib><creatorcontrib>Cuccaro, Michael L.</creatorcontrib><creatorcontrib>Bennett, David A.</creatorcontrib><creatorcontrib>Crane, Paul K.</creatorcontrib><creatorcontrib>Kamboh, M. Ilyas</creatorcontrib><creatorcontrib>Kukull, Walter A.</creatorcontrib><creatorcontrib>Au, Rhoda</creatorcontrib><creatorcontrib>Haines, Jonathan L.</creatorcontrib><creatorcontrib>Pericak‐Vance, Margaret A.</creatorcontrib><creatorcontrib>Schellenberg, Gerard D.</creatorcontrib><creatorcontrib>Mayeux, Richard</creatorcontrib><creatorcontrib>Lunetta, Kathryn L.</creatorcontrib><creatorcontrib>Farrer, Lindsay A.</creatorcontrib><creatorcontrib>Mez, Jesse</creatorcontrib><collection>Wiley Online Library Open Access</collection><collection>Wiley Free Content</collection><collection>CrossRef</collection><jtitle>Alzheimer's & dementia</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Dacey, Ryan</au><au>Han, Xudong</au><au>Moore, Mackenzie R</au><au>Chung, Jaeyoon</au><au>Durape, Shruti</au><au>Rosenthaler, Max</au><au>Uretsky, Madeline</au><au>Abdolmohammadi, Bobak</au><au>Lee, Annie J.</au><au>Brickman, Adam M.</au><au>Hohman, Timothy J.</au><au>Cuccaro, Michael L.</au><au>Bennett, David A.</au><au>Crane, Paul K.</au><au>Kamboh, M. Ilyas</au><au>Kukull, Walter A.</au><au>Au, Rhoda</au><au>Haines, Jonathan L.</au><au>Pericak‐Vance, Margaret A.</au><au>Schellenberg, Gerard D.</au><au>Mayeux, Richard</au><au>Lunetta, Kathryn L.</au><au>Farrer, Lindsay A.</au><au>Mez, Jesse</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Genome‐wide Interaction and Stratified Study with Smoking Identifies Association of APAF1 and MIXL1/LIN9 with Alzheimer’s Disease</atitle><jtitle>Alzheimer's & dementia</jtitle><date>2024-12</date><risdate>2024</risdate><volume>20</volume><issue>S1</issue><epage>n/a</epage><issn>1552-5260</issn><eissn>1552-5279</eissn><abstract>Background
Alzheimer’s disease (AD) has both genetic and environmental risk factors. Gene‐environment interaction may help explain some missing heritability. There is strong evidence for cigarette smoking as a risk factor for AD. To identify genetic‐smoking‐related associations with AD, we conducted a genome‐wide association study (GWAS) assessing a SNP‐smoking interaction and stratified analysis by smoking status.
Method
Lifetime smoking data were available and analyzed among 22,030 non‐Hispanic White (NHW; 8,232 cases; 13,798 controls) and 3,126 African American (AFA; 921 cases; 2,205 controls) participants from the AD Genetic Consortium and the Framingham Heart Study. “Ever smoking” status was considered as a dichotomous exposure, defined by current smoking status or past history of smoking. Across 35 datasets, we conducted GWAS with two approaches: inclusion of a SNP‐by‐smoking interaction term and stratification by smoking status (12,080 smokers, 13,428 non‐smokers). MAGEE was used to estimate SNP‐by‐smoking interaction effects and SAIGE was used to estimate SNP effects in stratified analysis. Age, sex, and principal components for population structure were included as covariates. METAL was used for inverse‐variance weighted meta‐analysis across datasets to estimate within‐ and cross‐ancestry effects.
Result
The stratified analysis identified a genome‐wide significant association among smokers in APAF1 on chromosome 12 (top SNP: rs12368451; smokers: MAF = 0.44, p = 2.2 × 10‐8, OR = 1.20; non‐smokers: MAF = 0.44, p = 0.97, OR = 1.00). Effects were present in both ancestry groups (NHW: MAF = 0.45, p = 6.1 × 10‐6, OR = 1.16; AFA: MAF = 0.35, p = 6.6 × 10‐5, OR = 1.46). APAF1 has been linked to gene‐smoking interaction for non‐AD related outcomes. A neighboring gene, ANKS1B, is highly expressed in the brain, interacts with amyloid‐b precursor protein, and has shown GWAS signals for smoking initiation and cognitive ability. We also identified a genome‐wide significant SNP‐by‐smoking interaction in the MIXL1/LIN9 region on chromosome 1 (top SNP: rs1091961, MAF = 0.35, p = 4.9 × 10‐8, βSNP*smoking = 0.24; smokers: OR = 1.12, p = 0.0006; non‐smokers: OR = 0.89, p = 0.0001). Within LIN9, several SNPs in linkage disequilibrium with rs1091961 have shown sub‐genome wide association with nicotine dependence.
Conclusion
In this gene‐smoking interaction and smoking‐stratified GWAS of AD, we identified two promising loci. These findings highlight the strength of utilizing cross‐ancestry datasets and considering both genetic and environmental factors together towards a personalized medicine approach to AD.</abstract><doi>10.1002/alz.091434</doi><tpages>2</tpages><oa>free_for_read</oa></addata></record> |
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| title | Genome‐wide Interaction and Stratified Study with Smoking Identifies Association of APAF1 and MIXL1/LIN9 with Alzheimer’s Disease |
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