Harmonization Initiative

Phenotype Harmonization 


About the ADSP-Phenotype Harmonization Consortium 

Initiated in 2012, the Alzheimer’s Disease (AD) Sequencing Project (ADSP) focuses on identifying novel genes driving risk and resilience in AD and related dementias (ADRD). To date, ADSP has curated sequencing data from 20,000+ individuals from 39 cohorts, which will increase to 100,000 participants across 70+ cohorts by 2023.ADSP has focused primarily on an AD case/control phenotype using clinical data. However, advancements in our understanding of AD and movement towards a biological definition that integrates pathological and neurodegenerative aspects of the disease, many of which precede clinical symptoms by decades, has presented an opportunity and pressing need to integrate rich endophenotypic data and characterize the genetic architecture of these complex biological cascades in ADRD. 

The ADSP Phenotype Harmonization Consortium (ADSP-PHC, U24-AG074855) was established to harmonize the rich endophenotype data across cohort studies to enable modern genomic analyses of ADRD. The ultimate goal of the ADSP-PHC is to generate harmonized data that will become a “legacy” dataset perpetually curated and shared through an established central data repository.  

  • Work in coordination with other ADSP workgroups and initiatives to streamline access to endophenotype data, provide high quality phenotype harmonization across domains, and provide comprehensive documentation of both data availability and harmonization procedures.  

  • The ADSP-PHC is committed to providing resources to the research community to facilitate the use of harmonized data. To date, ADSP-PHC investigators have held workshops in coordination with ISTAART and AAIC, and the links below serve as a resource library for these harmonization efforts. It is our goal that the increased use of the ADSP’s rich endophenotype data as a result of harmonization will provide a venue for investigators to learn and exchange innovation harmonization approaches to accelerate the identification of novel targets for therapeutic intervention in ADRD. 


    Data Explorer:


    ADSP Release Details:


    ADSP: The Basics of Data Harmonization


    1. Hampton OL, Mukherjee S, Properzi MJ, Schultz AP, Crane PK, Gibbons LE, Hohman TJ, Maruff P, Lim YY, Amariglio RE, Papp KV, Johnson KA, Rentz DM, Sperling RA, Buckley RF. Harmonizing the preclinical Alzheimer cognitive composite for multicohort studies. Neuropsychology. 2023 May;37(4):436-449. doi: 10.1037/neu0000833. Epub 2022 Jul 21. PMID: 35862098; PMCID: PMC9859944.


    2. Mukherjee S, Choi SE, Lee ML, Scollard P, Trittschuh EH, Mez J, Saykin AJ, Gibbons LE, Sanders RE, Zaman AF, Teylan MA, Kukull WA, Barnes LL, Bennett DA, Lacroix AZ, Larson EB, Cuccaro M, Mercado S, Dumitrescu L, Hohman TJ, Crane PK. Cognitive domain harmonization and cocalibration in studies of older adults. Neuropsychology. 2023 May;37(4):409-423. doi: 10.1037/neu0000835. Epub 2022 Aug 4. PMID: 35925737; PMCID: PMC9898463.


    3. Wortha SM, Frenzel S, Bahls M, Habes M, Wittfeld K, Van der Auwera S, Bülow R, Zylla S, Friedrich N, Nauck M, Völzke H, Grabe HJ, Schwarz C, Flöel A. Association of spermidine plasma levels with brain aging in a population-based study. Alzheimers Dement. 2023 May;19(5):1832-1840. doi: 10.1002/alz.12815. Epub 2022 Nov 2. PMID: 36321615.


    4. Eissman JM, Wells G, Khan OA, Liu D, Petyuk VA, Gifford KA, Dumitrescu L, Jefferson AL, Hohman TJ. Polygenic resilience score may be sensitive to preclinical Alzheimer's disease changes. Pac Symp Biocomput. 2023;28:449-460. PMID: 36540999; PMCID: PMC9888419.


    5. Evans TE, Knol MJ, Schwingenschuh P, Wittfeld K, Hilal S, Ikram MA, Dubost F, van Wijnen KMH, Katschnig P, Yilmaz P, de Bruijne M, Habes M, Chen C, Langer S, Völzke H, Ikram MK, Grabe HJ, Schmidt R, Adams HHH, Vernooij MW. Determinants of Perivascular Spaces in the General Population: A Pooled Cohort Analysis of Individual Participant Data. Neurology. 2023 Jan 10;100(2):e107-e122. doi: 10.1212/WNL.0000000000201349. Epub 2022 Oct 17. PMID: 36253103; PMCID: PMC9841448.
    6. Rashid T, Li K, Toledo JB, Nasrallah I, Pajewski NM, Dolui S, Detre J, Wolk DA, Liu H, Heckbert SR, Bryan RN, Williamson J, Davatzikos C, Seshadri S, Launer LJ, Habes M. Association of Intensive vs Standard Blood Pressure Control With Regional Changes in Cerebral Small Vessel Disease Biomarkers: Post Hoc Secondary Analysis of the SPRINT MIND Randomized Clinical Trial. JAMA Netw Open. 2023 Mar 1;6(3):e231055. doi: 10.1001/jamanetworkopen.2023.1055. PMID: 36857053; PMCID: PMC9978954.
    7. Klingenberg M, Stark D, Eitel F, Budding C, Habes M, Ritter K; Alzheimer’s Disease Neuroimaging Initiative. Higher performance for women than men in MRI-based Alzheimer's disease detection. Alzheimers Res Ther. 2023 Apr 20;15(1):84. doi: 10.1186/s13195-023-01225-6. PMID: 37081528; PMCID: PMC10116672.


    8. Archer DB, Schilling K, Shashikumar N, Jasodanand V, Moore EE, Pechman KR, Bilgel M, Beason-Held LL, An Y, Shafer A, Ferrucci L, Risacher SL, Gifford KA, Landman BA, Jefferson AL, Saykin AJ, Resnick SM, Hohman TJ; Alzheimer’s Disease Neuroimaging Initiative. Leveraging longitudinal diffusion MRI data to quantify differences in white matter microstructural decline in normal and abnormal aging. bioRxiv [Preprint]. 2023 May 18:2023.05.17.541182. doi: 10.1101/2023.05.17.541182. Update in: Alzheimers Dement (Amst). 2023 Sep 29;15(4):e12468. PMID: 37292885; PMCID: PMC10245725.


    9. Charisis S, Rashid T, Liu H, Ware JB, Jensen PN, Austin TR, Li K, Fadaee E, Hilal S, Chen C, Hughes TM, Romero JR, Toledo JB, Longstreth WT Jr, Hohman TJ, Nasrallah I, Bryan RN, Launer LJ, Davatzikos C, Seshadri S, Heckbert SR, Habes M. Assessment of Risk Factors and Clinical Importance of Enlarged Perivascular Spaces by Whole-Brain Investigation in the Multi-Ethnic Study of Atherosclerosis. JAMA Netw Open. 2023 Apr 3;6(4):e239196. doi: 10.1001/jamanetworkopen.2023.9196. PMID: 37093602; PMCID: PMC10126873.


    10. Wang D, Honnorat N, Fox PT, Ritter K, Eickhoff SB, Seshadri S; Alzheimer’s Disease Neuroimaging Initiative; Habes M. Deep neural network heatmaps capture Alzheimer's disease patterns reported in a large meta-analysis of neuroimaging studies. Neuroimage. 2023 Apr 1;269:119929. doi: 10.1016/j.neuroimage.2023.119929. Epub 2023 Feb 4. PMID: 36740029.


    11. Brenowitz WD, Fornage M, Launer LJ, Habes M, Davatzikos C, Yaffe K. Alzheimer's Disease Genetic Risk, Cognition, and Brain Aging in Midlife. Ann Neurol. 2023 Mar;93(3):629-634. doi: 10.1002/ana.26569. Epub 2022 Dec 25. PMID: 36511390; PMCID: PMC9974745.


    12. Tosun D, Thropp P, Southekal S, Spottiswoode B, Fahmi R; Alzheimer's Disease Neuroimaging Initiative. Profiling and predicting distinct tau progression patterns: An unsupervised data-driven approach to flortaucipir positron emission tomography. Alzheimers Dement. 2023 Jun 8. doi: 10.1002/alz.13164. Epub ahead of print. PMID: 37288753.


    13. Toledo JB, Rashid T, Liu H, Launer L, Shaw LM, Heckbert SR, Weiner M, Seshadri S, Habes M; Alzheimer’s Disease Neuroimaging Initiative. SPARE-Tau: A flortaucipir machine-learning derived early predictor of cognitive decline. PLoS One. 2022 Nov 3;17(11):e0276392. doi: 10.1371/journal.pone.0276392. PMID: 36327215; PMCID: PMC9632811.


    14. Wells LF, Risacher SL, McDonald BC, Farlow MR, Brosch J, Gao S, Apostolova LG, Saykin AJ; Alzheimer’s Disease Neuroimaging Initiative. Measuring Subjective Cognitive Decline in Older Adults: Harmonization Between the Cognitive Change Index and the Measurement of Everyday Cognition Instruments. J Alzheimers Dis. 2022;87(2):761-769. doi: 10.3233/JAD-215388. PMID: 35367962; PMCID: PMC9169561.


    15. Eissman JM, Dumitrescu L, Mahoney ER, Smith AN, Mukherjee S, Lee ML, Scollard P, Choi SE, Bush WS, Engelman CD, Lu Q, Fardo DW, Trittschuh EH, Mez J, Kaczorowski CC, Hernandez Saucedo H, Widaman KF, Buckley RF, Properzi MJ, Mormino EC, Yang HS, Harrison TM, Hedden T, Nho K, Andrews SJ, Tommet D, Hadad N, Sanders RE, Ruderfer DM, Gifford KA, Zhong X, Raghavan NS, Vardarajan BN; Alzheimer’s Disease Neuroimaging Initiative (ADNI); Alzheimer’s Disease Genetics Consortium (ADGC); A4 Study Team; Pericak-Vance MA, Farrer LA, Wang LS, Cruchaga C, Schellenberg GD, Cox NJ, Haines JL, Keene CD, Saykin AJ, Larson EB, Sperling RA, Mayeux R, Cuccaro ML, Bennett DA, Schneider JA, Crane PK, Jefferson AL, Hohman TJ. Sex differences in the genetic architecture of cognitive resilience to Alzheimer's disease. Brain. 2022 Jul 29;145(7):2541-2554. doi: 10.1093/brain/awac177. PMID: 35552371; PMCID: PMC9337804.


    16. Walters S, Contreras AG, Eissman JM, Mukherjee S, Lee ML, Choi SE, Scollard P, Trittschuh EH, Mez JB, Bush WS, Kunkle BW, Naj AC, Peterson A, Gifford KA, Cuccaro ML, Cruchaga C, Pericak-Vance MA, Farrer LA, Wang LS, Haines JL, Jefferson AL, Kukull WA, Keene CD, Saykin AJ, Thompson PM, Martin ER, Bennett DA, Barnes LL, Schneider JA, Crane PK, Hohman TJ, Dumitrescu L; Alzheimer’s Disease Neuroimaging Initiative, Alzheimer’s Disease Genetics Consortium, and Alzheimer’s Disease Sequencing Project. Associations of Sex, Race, and Apolipoprotein E Alleles With Multiple Domains of Cognition Among Older Adults. JAMA Neurol. 2023 Sep 1;80(9):929-939. doi: 10.1001/jamaneurol.2023.2169. PMID: 37459083; PMCID: PMC10352930.


    17. Kang M, Ang TFA, Devine SA, Sherva R, Mukherjee S, Trittschuh EH, Gibbons LE, Scollard P, Lee M, Choi SE, Klinedinst B, Nakano C, Dumitrescu LC, Durant A, Hohman TJ, Cuccaro ML, Saykin AJ, Kukull WA, Bennett DA, Wang LS, Mayeux RP, Haines JL, Pericak-Vance MA, Schellenberg GD, Crane PK, Au R, Lunetta KL, Mez JB, Farrer LA. A genome-wide search for pleiotropy in more than 100,000 harmonized longitudinal cognitive domain scores. Mol Neurodegener. 2023 Jun 22;18(1):40. doi: 10.1186/s13024-023-00633-4. PMID: 37349795; PMCID: PMC10286470.
  • The ADSP-PHC is led by MPI Team Dr. Timothy Hohman (Vanderbilt University Medical Center), Dr. Michael Cuccaro (University of Miami) and Dr. Arthur Toga (University of Southern California). Our multi-disciplinary team includes world experts in neuroimaging, neuropsychology, fluid biomarkers, neuropathology, and vascular contributions to ADRD.