There are many active research projects accessing and applying shared ADNI data. Use the search above to find specific research focuses on the active ADNI investigations. This information is requested annually as a requirement for data access.
| Principal Investigator | |
| Principal Investigator's Name: | Rosa Rademakers |
| Institution: | Mayo Clinic |
| Department: | Neuroscience |
| Country: | |
| Proposed Analysis: | Due to the complex phenotypic presentation, patients with frontotemporal dementia (FTD) are often misdiagnosed for AD. We hypothesize that patients with AD and FTD share common genetics factor. We generated whole genome sequencing data from 517 FTD patients and 838 controls and recently demonstrated that genetic variants at the HLA locus, on top of being associated with AD, are associated with FTD. This adds to the growing body of genetic factors that are associated with both disease such as TREM2, MAPT, GRN and C9ORF72. We have now extended our cohort of whole genome sequenced FTD and controls. Our work builds on the hypothesis that Alzheimer’s disease and related dementias have common pathways underlying their pathology. We are requesting access to both the raw files and the summarized variants (VCF) of the Alzheimer's Disease Sequence Project (ADSP) whole-genome sequencing data set to increase our statistical power and to follow-up findings from our whole-genome sequencing studies related to Frontotemporal dementia (FTD). As part of the ADSP dataset originates from ADNi we are requesting access to both instances. We will combine our data with ADSP’s data in order to improve statistical power in our association analyses by adding ADSP controls and to assess genetic risks associated with FTD in the patient population of ADSP. Our plan is to stratify the data by disease status and age at onset (early onset and late-onset AD) and to perform the analyses in the total cohort as well as the sub cohorts. 1. We will call variants combining our FTD data with ADSP data starting from the raw files and using the same pipeline as the one already used for our FTD genome data. Briefly, ADSP raw files will be processed through the Mayo Clinic Genome-GPS (GGPS) analytic pipeline and the ANNOVAR variant annotation pipeline. The GGPS pipeline is widely used for different next-generation sequencing projects at the Mayo Clinic and is constantly updated with the newest public databases and resources. Our GGPS pipeline also includes the calling of copy number variant by Breakdancer but is versatile enough to incorporate any new structural variant caller. In addition, we will also run the ADSP’s data with specific pipelines more accurately for complex genomic regions such as the HLA risk region, e.g. HISAT2. 2. We will utilize several commonly used software programs, such as Plink-seq and SKAT package, to perform our association analyses. First, control data will be used to perform a large association study on FTD patients and controls. Second, association studies within the ADSP dataset will be performed. All analyses will be done at the single variant, gene, and structural variant levels. Finally, pathway analyses will be performed in our FTD dataset and ADSP for comparison. Using these approaches, we hope to identify novel mutations/genes/pathways that are related to both AD and FTD and will benefit the larger scientific community working on neurodegenerative disorders. |
| Additional Investigators | |
| Investigator's Name: | Cyril Pottier |
| Proposed Analysis: | Due to the complex phenotypic presentation, patients with frontotemporal dementia (FTD) are often misdiagnosed for AD. We hypothesize that patients with AD and FTD share common genetics factor. We generated whole genome sequencing data from 517 FTD patients and 838 controls and recently demonstrated that genetic variants at the HLA locus, on top of being associated with AD, are associated with FTD. This adds to the growing body of genetic factors that are associated with both disease such as TREM2, MAPT, GRN and C9ORF72. We have now extended our cohort of whole genome sequenced FTD and controls. Our work builds on the hypothesis that Alzheimer’s disease and related dementias have common pathways underlying their pathology. We are requesting access to both the raw files and the summarized variants (VCF) of the Alzheimer's Disease Sequence Project (ADSP) whole-genome sequencing data set to increase our statistical power and to follow-up findings from our whole-genome sequencing studies related to Frontotemporal dementia (FTD). As part of the ADSP dataset originates from ADNi we are requesting access to both instances. We will combine our data with ADSP’s data in order to improve statistical power in our association analyses by adding ADSP controls and to assess genetic risks associated with FTD in the patient population of ADSP. Our plan is to stratify the data by disease status and age at onset (early onset and late-onset AD) and to perform the analyses in the total cohort as well as the sub cohorts. 1. We will call variants combining our FTD data with ADSP data starting from the raw files and using the same pipeline as the one already used for our FTD genome data. Briefly, ADSP raw files will be processed through the Mayo Clinic Genome-GPS (GGPS) analytic pipeline and the ANNOVAR variant annotation pipeline. The GGPS pipeline is widely used for different next-generation sequencing projects at the Mayo Clinic and is constantly updated with the newest public databases and resources. Our GGPS pipeline also includes the calling of copy number variant by Breakdancer but is versatile enough to incorporate any new structural variant caller. In addition, we will also run the ADSP’s data with specific pipelines more accurately for complex genomic regions such as the HLA risk region, e.g. HISAT2. 2. We will utilize several commonly used software programs, such as Plink-seq and SKAT package, to perform our association analyses. First, control data will be used to perform a large association study on FTD patients and controls. Second, association studies within the ADSP dataset will be performed. All analyses will be done at the single variant, gene, and structural variant levels. Finally, pathway analyses will be performed in our FTD dataset and ADSP for comparison. Using these approaches, we hope to identify novel mutations/genes/pathways that are related to both AD and FTD and will benefit the larger scientific community working on neurodegenerative disorders. |
| Investigator's Name: | Joanna Biernacka |
| Proposed Analysis: | Due to the complex phenotypic presentation, patients with frontotemporal dementia (FTD) are often misdiagnosed for AD. We hypothesize that patients with AD and FTD share common genetics factor. We generated whole genome sequencing data from 517 FTD patients and 838 controls and recently demonstrated that genetic variants at the HLA locus, on top of being associated with AD, are associated with FTD. This adds to the growing body of genetic factors that are associated with both disease such as TREM2, MAPT, GRN and C9ORF72. We have now extended our cohort of whole genome sequenced FTD and controls. Our work builds on the hypothesis that Alzheimer’s disease and related dementias have common pathways underlying their pathology. We are requesting access to both the raw files and the summarized variants (VCF) of the Alzheimer's Disease Sequence Project (ADSP) whole-genome sequencing data set to increase our statistical power and to follow-up findings from our whole-genome sequencing studies related to Frontotemporal dementia (FTD). As part of the ADSP dataset originates from ADNi we are requesting access to both instances. We will combine our data with ADSP’s data in order to improve statistical power in our association analyses by adding ADSP controls and to assess genetic risks associated with FTD in the patient population of ADSP. Our plan is to stratify the data by disease status and age at onset (early onset and late-onset AD) and to perform the analyses in the total cohort as well as the sub cohorts. 1. We will call variants combining our FTD data with ADSP data starting from the raw files and using the same pipeline as the one already used for our FTD genome data. Briefly, ADSP raw files will be processed through the Mayo Clinic Genome-GPS (GGPS) analytic pipeline and the ANNOVAR variant annotation pipeline. The GGPS pipeline is widely used for different next-generation sequencing projects at the Mayo Clinic and is constantly updated with the newest public databases and resources. Our GGPS pipeline also includes the calling of copy number variant by Breakdancer but is versatile enough to incorporate any new structural variant caller. In addition, we will also run the ADSP’s data with specific pipelines more accurately for complex genomic regions such as the HLA risk region, e.g. HISAT2. 2. We will utilize several commonly used software programs, such as Plink-seq and SKAT package, to perform our association analyses. First, control data will be used to perform a large association study on FTD patients and controls. Second, association studies within the ADSP dataset will be performed. All analyses will be done at the single variant, gene, and structural variant levels. Finally, pathway analyses will be performed in our FTD dataset and ADSP for comparison. Using these approaches, we hope to identify novel mutations/genes/pathways that are related to both AD and FTD and will benefit the larger scientific community working on neurodegenerative disorders. |
| Investigator's Name: | Anthony Batzler |
| Proposed Analysis: | Due to the complex phenotypic presentation, patients with frontotemporal dementia (FTD) are often misdiagnosed for AD. We hypothesize that patients with AD and FTD share common genetics factor. We generated whole genome sequencing data from 517 FTD patients and 838 controls and recently demonstrated that genetic variants at the HLA locus, on top of being associated with AD, are associated with FTD. This adds to the growing body of genetic factors that are associated with both disease such as TREM2, MAPT, GRN and C9ORF72. We have now extended our cohort of whole genome sequenced FTD and controls. Our work builds on the hypothesis that Alzheimer’s disease and related dementias have common pathways underlying their pathology. We are requesting access to both the raw files and the summarized variants (VCF) of the Alzheimer's Disease Sequence Project (ADSP) whole-genome sequencing data set to increase our statistical power and to follow-up findings from our whole-genome sequencing studies related to Frontotemporal dementia (FTD). As part of the ADSP dataset originates from ADNi we are requesting access to both instances. We will combine our data with ADSP’s data in order to improve statistical power in our association analyses by adding ADSP controls and to assess genetic risks associated with FTD in the patient population of ADSP. Our plan is to stratify the data by disease status and age at onset (early onset and late-onset AD) and to perform the analyses in the total cohort as well as the sub cohorts. 1. We will call variants combining our FTD data with ADSP data starting from the raw files and using the same pipeline as the one already used for our FTD genome data. Briefly, ADSP raw files will be processed through the Mayo Clinic Genome-GPS (GGPS) analytic pipeline and the ANNOVAR variant annotation pipeline. The GGPS pipeline is widely used for different next-generation sequencing projects at the Mayo Clinic and is constantly updated with the newest public databases and resources. Our GGPS pipeline also includes the calling of copy number variant by Breakdancer but is versatile enough to incorporate any new structural variant caller. In addition, we will also run the ADSP’s data with specific pipelines more accurately for complex genomic regions such as the HLA risk region, e.g. HISAT2. 2. We will utilize several commonly used software programs, such as Plink-seq and SKAT package, to perform our association analyses. First, control data will be used to perform a large association study on FTD patients and controls. Second, association studies within the ADSP dataset will be performed. All analyses will be done at the single variant, gene, and structural variant levels. Finally, pathway analyses will be performed in our FTD dataset and ADSP for comparison. Using these approaches, we hope to identify novel mutations/genes/pathways that are related to both AD and FTD and will benefit the larger scientific community working on neurodegenerative disorders. |
| Investigator's Name: | Gregory Jenkins |
| Proposed Analysis: | Due to the complex phenotypic presentation, patients with frontotemporal dementia (FTD) are often misdiagnosed for AD. We hypothesize that patients with AD and FTD share common genetics factor. We generated whole genome sequencing data from 517 FTD patients and 838 controls and recently demonstrated that genetic variants at the HLA locus, on top of being associated with AD, are associated with FTD. This adds to the growing body of genetic factors that are associated with both disease such as TREM2, MAPT, GRN and C9ORF72. We have now extended our cohort of whole genome sequenced FTD and controls. Our work builds on the hypothesis that Alzheimer’s disease and related dementias have common pathways underlying their pathology. We are requesting access to both the raw files and the summarized variants (VCF) of the Alzheimer's Disease Sequence Project (ADSP) whole-genome sequencing data set to increase our statistical power and to follow-up findings from our whole-genome sequencing studies related to Frontotemporal dementia (FTD). As part of the ADSP dataset originates from ADNi we are requesting access to both instances. We will combine our data with ADSP’s data in order to improve statistical power in our association analyses by adding ADSP controls and to assess genetic risks associated with FTD in the patient population of ADSP. Our plan is to stratify the data by disease status and age at onset (early onset and late-onset AD) and to perform the analyses in the total cohort as well as the sub cohorts. 1. We will call variants combining our FTD data with ADSP data starting from the raw files and using the same pipeline as the one already used for our FTD genome data. Briefly, ADSP raw files will be processed through the Mayo Clinic Genome-GPS (GGPS) analytic pipeline and the ANNOVAR variant annotation pipeline. The GGPS pipeline is widely used for different next-generation sequencing projects at the Mayo Clinic and is constantly updated with the newest public databases and resources. Our GGPS pipeline also includes the calling of copy number variant by Breakdancer but is versatile enough to incorporate any new structural variant caller. In addition, we will also run the ADSP’s data with specific pipelines more accurately for complex genomic regions such as the HLA risk region, e.g. HISAT2. 2. We will utilize several commonly used software programs, such as Plink-seq and SKAT package, to perform our association analyses. First, control data will be used to perform a large association study on FTD patients and controls. Second, association studies within the ADSP dataset will be performed. All analyses will be done at the single variant, gene, and structural variant levels. Finally, pathway analyses will be performed in our FTD dataset and ADSP for comparison. Using these approaches, we hope to identify novel mutations/genes/pathways that are related to both AD and FTD and will benefit the larger scientific community working on neurodegenerative disorders. |
| Investigator's Name: | Yan Asmann |
| Proposed Analysis: | Due to the complex phenotypic presentation, patients with frontotemporal dementia (FTD) are often misdiagnosed for AD. We hypothesize that patients with AD and FTD share common genetics factor. We generated whole genome sequencing data from 517 FTD patients and 838 controls and recently demonstrated that genetic variants at the HLA locus, on top of being associated with AD, are associated with FTD. This adds to the growing body of genetic factors that are associated with both disease such as TREM2, MAPT, GRN and C9ORF72. We have now extended our cohort of whole genome sequenced FTD and controls. Our work builds on the hypothesis that Alzheimer’s disease and related dementias have common pathways underlying their pathology. We are requesting access to both the raw files and the summarized variants (VCF) of the Alzheimer's Disease Sequence Project (ADSP) whole-genome sequencing data set to increase our statistical power and to follow-up findings from our whole-genome sequencing studies related to Frontotemporal dementia (FTD). As part of the ADSP dataset originates from ADNi we are requesting access to both instances. We will combine our data with ADSP’s data in order to improve statistical power in our association analyses by adding ADSP controls and to assess genetic risks associated with FTD in the patient population of ADSP. Our plan is to stratify the data by disease status and age at onset (early onset and late-onset AD) and to perform the analyses in the total cohort as well as the sub cohorts. 1. We will call variants combining our FTD data with ADSP data starting from the raw files and using the same pipeline as the one already used for our FTD genome data. Briefly, ADSP raw files will be processed through the Mayo Clinic Genome-GPS (GGPS) analytic pipeline and the ANNOVAR variant annotation pipeline. The GGPS pipeline is widely used for different next-generation sequencing projects at the Mayo Clinic and is constantly updated with the newest public databases and resources. Our GGPS pipeline also includes the calling of copy number variant by Breakdancer but is versatile enough to incorporate any new structural variant caller. In addition, we will also run the ADSP’s data with specific pipelines more accurately for complex genomic regions such as the HLA risk region, e.g. HISAT2. 2. We will utilize several commonly used software programs, such as Plink-seq and SKAT package, to perform our association analyses. First, control data will be used to perform a large association study on FTD patients and controls. Second, association studies within the ADSP dataset will be performed. All analyses will be done at the single variant, gene, and structural variant levels. Finally, pathway analyses will be performed in our FTD dataset and ADSP for comparison. Using these approaches, we hope to identify novel mutations/genes/pathways that are related to both AD and FTD and will benefit the larger scientific community working on neurodegenerative disorders. |
| Investigator's Name: | Yingxue Ren |
| Proposed Analysis: | Due to the complex phenotypic presentation, patients with frontotemporal dementia (FTD) are often misdiagnosed for AD. We hypothesize that patients with AD and FTD share common genetics factor. We generated whole genome sequencing data from 517 FTD patients and 838 controls and recently demonstrated that genetic variants at the HLA locus, on top of being associated with AD, are associated with FTD. This adds to the growing body of genetic factors that are associated with both disease such as TREM2, MAPT, GRN and C9ORF72. We have now extended our cohort of whole genome sequenced FTD and controls. Our work builds on the hypothesis that Alzheimer’s disease and related dementias have common pathways underlying their pathology. We are requesting access to both the raw files and the summarized variants (VCF) of the Alzheimer's Disease Sequence Project (ADSP) whole-genome sequencing data set to increase our statistical power and to follow-up findings from our whole-genome sequencing studies related to Frontotemporal dementia (FTD). As part of the ADSP dataset originates from ADNi we are requesting access to both instances. We will combine our data with ADSP’s data in order to improve statistical power in our association analyses by adding ADSP controls and to assess genetic risks associated with FTD in the patient population of ADSP. Our plan is to stratify the data by disease status and age at onset (early onset and late-onset AD) and to perform the analyses in the total cohort as well as the sub cohorts. 1. We will call variants combining our FTD data with ADSP data starting from the raw files and using the same pipeline as the one already used for our FTD genome data. Briefly, ADSP raw files will be processed through the Mayo Clinic Genome-GPS (GGPS) analytic pipeline and the ANNOVAR variant annotation pipeline. The GGPS pipeline is widely used for different next-generation sequencing projects at the Mayo Clinic and is constantly updated with the newest public databases and resources. Our GGPS pipeline also includes the calling of copy number variant by Breakdancer but is versatile enough to incorporate any new structural variant caller. In addition, we will also run the ADSP’s data with specific pipelines more accurately for complex genomic regions such as the HLA risk region, e.g. HISAT2. 2. We will utilize several commonly used software programs, such as Plink-seq and SKAT package, to perform our association analyses. First, control data will be used to perform a large association study on FTD patients and controls. Second, association studies within the ADSP dataset will be performed. All analyses will be done at the single variant, gene, and structural variant levels. Finally, pathway analyses will be performed in our FTD dataset and ADSP for comparison. Using these approaches, we hope to identify novel mutations/genes/pathways that are related to both AD and FTD and will benefit the larger scientific community working on neurodegenerative disorders. |
| Investigator's Name: | James Hildebrand |
| Proposed Analysis: | Due to the complex phenotypic presentation, patients with frontotemporal dementia (FTD) are often misdiagnosed for AD. We hypothesize that patients with AD and FTD share common genetics factor. We generated whole genome sequencing data from 517 FTD patients and 838 controls and recently demonstrated that genetic variants at the HLA locus, on top of being associated with AD, are associated with FTD. This adds to the growing body of genetic factors that are associated with both disease such as TREM2, MAPT, GRN and C9ORF72. We have now extended our cohort of whole genome sequenced FTD and controls. Our work builds on the hypothesis that Alzheimer’s disease and related dementias have common pathways underlying their pathology. We are requesting access to both the raw files and the summarized variants (VCF) of the Alzheimer's Disease Sequence Project (ADSP) whole-genome sequencing data set to increase our statistical power and to follow-up findings from our whole-genome sequencing studies related to Frontotemporal dementia (FTD). As part of the ADSP dataset originates from ADNi we are requesting access to both instances. We will combine our data with ADSP’s data in order to improve statistical power in our association analyses by adding ADSP controls and to assess genetic risks associated with FTD in the patient population of ADSP. Our plan is to stratify the data by disease status and age at onset (early onset and late-onset AD) and to perform the analyses in the total cohort as well as the sub cohorts. 1. We will call variants combining our FTD data with ADSP data starting from the raw files and using the same pipeline as the one already used for our FTD genome data. Briefly, ADSP raw files will be processed through the Mayo Clinic Genome-GPS (GGPS) analytic pipeline and the ANNOVAR variant annotation pipeline. The GGPS pipeline is widely used for different next-generation sequencing projects at the Mayo Clinic and is constantly updated with the newest public databases and resources. Our GGPS pipeline also includes the calling of copy number variant by Breakdancer but is versatile enough to incorporate any new structural variant caller. In addition, we will also run the ADSP’s data with specific pipelines more accurately for complex genomic regions such as the HLA risk region, e.g. HISAT2. 2. We will utilize several commonly used software programs, such as Plink-seq and SKAT package, to perform our association analyses. First, control data will be used to perform a large association study on FTD patients and controls. Second, association studies within the ADSP dataset will be performed. All analyses will be done at the single variant, gene, and structural variant levels. Finally, pathway analyses will be performed in our FTD dataset and ADSP for comparison. Using these approaches, we hope to identify novel mutations/genes/pathways that are related to both AD and FTD and will benefit the larger scientific community working on neurodegenerative disorders. |
