Browsing by Author "Habes, Mohamad"
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Item A deep learning framework identifies dimensional representations of Alzheimer’s Disease from brain structure(Springer Nature, 2021-12-03) Yang, Zhijian; Nasrallah, Ilya M.; Shou, Haochang; Wen, Junhao; Doshi, Jimit; Habes, Mohamad; Erus, Guray; Abdulkadir, Ahmed; Resnick, Susan M.; Albert, Marilyn S.; Maruff, Paul; Fripp, Jurgen; Morris, John C.; Wolk, David A.; Davatzikos, Christos; iSTAGING Consortium; Baltimore Longitudinal Study of Aging (BLSA); Alzheimer’s Disease Neuroimaging Initiative (ADNI); Radiology and Imaging Sciences, School of MedicineHeterogeneity of brain diseases is a challenge for precision diagnosis/prognosis. We describe and validate Smile-GAN (SeMI-supervised cLustEring-Generative Adversarial Network), a semi-supervised deep-clustering method, which examines neuroanatomical heterogeneity contrasted against normal brain structure, to identify disease subtypes through neuroimaging signatures. When applied to regional volumes derived from T1-weighted MRI (two studies; 2,832 participants; 8,146 scans) including cognitively normal individuals and those with cognitive impairment and dementia, Smile-GAN identified four patterns or axes of neurodegeneration. Applying this framework to longitudinal data revealed two distinct progression pathways. Measures of expression of these patterns predicted the pathway and rate of future neurodegeneration. Pattern expression offered complementary performance to amyloid/tau in predicting clinical progression. These deep-learning derived biomarkers offer potential for precision diagnostics and targeted clinical trial recruitment.Item Characterizing Heterogeneity in Neuroimaging, Cognition, Clinical Symptoms, and Genetics Among Patients With Late-Life Depression(American Medical Association, 2022) Wen, Junhao; Fu, Cynthia H. Y.; Tosun, Duygu; Veturi, Yogasudha; Yang, Zhijian; Abdulkadir, Ahmed; Mamourian, Elizabeth; Srinivasan, Dhivya; Skampardoni, Ioanna; Singh, Ashish; Nawani, Hema; Bao, Jingxuan; Erus, Guray; Shou, Haochang; Habes, Mohamad; Doshi, Jimit; Varol, Erdem; Mackin, R. Scott; Sotiras, Aristeidis; Fan, Yong; Saykin, Andrew J.; Sheline, Yvette I.; Shen, Li; Ritchie, Marylyn D.; Wolk, David A.; Albert, Marilyn; Resnick, Susan M.; Davatzikos, Christos; iSTAGING consortium; ADNI; BIOCARD; BLSA; Radiology and Imaging Sciences, School of MedicineImportance: Late-life depression (LLD) is characterized by considerable heterogeneity in clinical manifestation. Unraveling such heterogeneity might aid in elucidating etiological mechanisms and support precision and individualized medicine. Objective: To cross-sectionally and longitudinally delineate disease-related heterogeneity in LLD associated with neuroanatomy, cognitive functioning, clinical symptoms, and genetic profiles. Design, setting, and participants: The Imaging-Based Coordinate System for Aging and Neurodegenerative Diseases (iSTAGING) study is an international multicenter consortium investigating brain aging in pooled and harmonized data from 13 studies with more than 35 000 participants, including a subset of individuals with major depressive disorder. Multimodal data from a multicenter sample (N = 996), including neuroimaging, neurocognitive assessments, and genetics, were analyzed in this study. A semisupervised clustering method (heterogeneity through discriminative analysis) was applied to regional gray matter (GM) brain volumes to derive dimensional representations. Data were collected from July 2017 to July 2020 and analyzed from July 2020 to December 2021. Main outcomes and measures: Two dimensions were identified to delineate LLD-associated heterogeneity in voxelwise GM maps, white matter (WM) fractional anisotropy, neurocognitive functioning, clinical phenotype, and genetics. Results: A total of 501 participants with LLD (mean [SD] age, 67.39 [5.56] years; 332 women) and 495 healthy control individuals (mean [SD] age, 66.53 [5.16] years; 333 women) were included. Patients in dimension 1 demonstrated relatively preserved brain anatomy without WM disruptions relative to healthy control individuals. In contrast, patients in dimension 2 showed widespread brain atrophy and WM integrity disruptions, along with cognitive impairment and higher depression severity. Moreover, 1 de novo independent genetic variant (rs13120336; chromosome: 4, 186387714; minor allele, G) was significantly associated with dimension 1 (odds ratio, 2.35; SE, 0.15; P = 3.14 ×108) but not with dimension 2. The 2 dimensions demonstrated significant single-nucleotide variant-based heritability of 18% to 27% within the general population (N = 12 518 in UK Biobank). In a subset of individuals having longitudinal measurements, those in dimension 2 experienced a more rapid longitudinal change in GM and brain age (Cohen f2 = 0.03; P = .02) and were more likely to progress to Alzheimer disease (Cohen f2 = 0.03; P = .03) compared with those in dimension 1 (N = 1431 participants and 7224 scans from the Alzheimer's Disease Neuroimaging Initiative [ADNI], Baltimore Longitudinal Study of Aging [BLSA], and Biomarkers for Older Controls at Risk for Dementia [BIOCARD] data sets). Conclusions and relevance: This study characterized heterogeneity in LLD into 2 dimensions with distinct neuroanatomical, cognitive, clinical, and genetic profiles. This dimensional approach provides a potential mechanism for investigating the heterogeneity of LLD and the relevance of the latent dimensions to possible disease mechanisms, clinical outcomes, and responses to interventions.Item Genetic and clinical correlates of two neuroanatomical AI dimensions in the Alzheimer's disease continuum(Springer Nature, 2024-10-05) Wen, Junhao; Yang, Zhijian; Nasrallah, Ilya M.; Cui, Yuhan; Erus, Guray; Srinivasan, Dhivya; Abdulkadir, Ahmed; Mamourian, Elizabeth; Hwang, Gyujoon; Singh, Ashish; Bergman, Mark; Bao, Jingxuan; Varol, Erdem; Zhou, Zhen; Boquet-Pujadas, Aleix; Chen, Jiong; Toga, Arthur W.; Saykin, Andrew J.; Hohman, Timothy J.; Thompson, Paul M.; Villeneuve, Sylvia; Gollub, Randy; Sotiras, Aristeidis; Wittfeld, Katharina; Grabe, Hans J.; Tosun, Duygu; Bilgel, Murat; An, Yang; Marcus, Daniel S.; LaMontagne, Pamela; Benzinger, Tammie L.; Heckbert, Susan R.; Austin, Thomas R.; Launer, Lenore J.; Espeland, Mark; Masters, Colin L.; Maruff, Paul; Fripp, Jurgen; Johnson, Sterling C.; Morris, John C.; Albert, Marilyn S.; Bryan, R. Nick; Resnick, Susan M.; Ferrucci, Luigi; Fan, Yong; Habes, Mohamad; Wolk, David; Shen, Li; Shou, Haochang; Davatzikos, Christos; Radiology and Imaging Sciences, School of MedicineAlzheimer's disease (AD) is associated with heterogeneous atrophy patterns. We employed a semi-supervised representation learning technique known as Surreal-GAN, through which we identified two latent dimensional representations of brain atrophy in symptomatic mild cognitive impairment (MCI) and AD patients: the "diffuse-AD" (R1) dimension shows widespread brain atrophy, and the "MTL-AD" (R2) dimension displays focal medial temporal lobe (MTL) atrophy. Critically, only R2 was associated with widely known sporadic AD genetic risk factors (e.g., APOE ε4) in MCI and AD patients at baseline. We then independently detected the presence of the two dimensions in the early stages by deploying the trained model in the general population and two cognitively unimpaired cohorts of asymptomatic participants. In the general population, genome-wide association studies found 77 genes unrelated to APOE differentially associated with R1 and R2. Functional analyses revealed that these genes were overrepresented in differentially expressed gene sets in organs beyond the brain (R1 and R2), including the heart (R1) and the pituitary gland, muscle, and kidney (R2). These genes were enriched in biological pathways implicated in dendritic cells (R2), macrophage functions (R1), and cancer (R1 and R2). Several of them were "druggable genes" for cancer (R1), inflammation (R1), cardiovascular diseases (R1), and diseases of the nervous system (R2). The longitudinal progression showed that APOE ε4, amyloid, and tau were associated with R2 at early asymptomatic stages, but this longitudinal association occurs only at late symptomatic stages in R1. Our findings deepen our understanding of the multifaceted pathogenesis of AD beyond the brain. In early asymptomatic stages, the two dimensions are associated with diverse pathological mechanisms, including cardiovascular diseases, inflammation, and hormonal dysfunction-driven by genes different from APOE-which may collectively contribute to the early pathogenesis of AD. All results are publicly available at https://labs-laboratory.com/medicine/ .Item Genomic loci influence patterns of structural covariance in the human brain(National Academy of Science, 2023) Wen, Junhao; Nasrallah, Ilya M.; Abdulkadir, Ahmed; Satterthwaite, Theodore D.; Yang, Zhijian; Erus, Guray; Robert-Fitzgerald, Timothy; Singh, Ashish; Sotiras, Aristeidis; Boquet-Pujadas, Aleix; Mamourian, Elizabeth; Doshi, Jimit; Cui, Yuhan; Srinivasan, Dhivya; Skampardoni, Ioanna; Chen, Jiong; Hwang, Gyujoon; Bergman, Mark; Bao, Jingxuan; Veturi, Yogasudha; Zhou, Zhen; Yang, Shu; Dazzan, Paola; Kahn, Rene S.; Schnack, Hugo G.; Zanetti, Marcus V.; Meisenzahl, Eva; Busatto, Geraldo F.; Crespo-Facorro, Benedicto; Pantelis, Christos; Wood, Stephen J.; Zhuo, Chuanjun; Shinohara, Russell T.; Gur, Ruben C.; Gur, Raquel E.; Koutsouleris, Nikolaos; Wolf, Daniel H.; Saykin, Andrew J.; Ritchie, Marylyn D.; Shen, Li; Thompson, Paul M.; Colliot, Olivier; Wittfeld, Katharina; Grabe, Hans J.; Tosun, Duygu; Bilgel, Murat; An, Yang; Marcus, Daniel S.; LaMontagne, Pamela; Heckbert, Susan R.; Austin, Thomas R.; Launer, Lenore J.; Espeland, Mark; Masters, Colin L.; Maruff, Paul; Fripp, Jurgen; Johnson, Sterling C.; Morris, John C.; Albert, Marilyn S.; Bryan, R. Nick; Resnick, Susan M.; Fan, Yong; Habes, Mohamad; Wolk, David; Shou, Haochang; Davatzikos, Christos; Radiology and Imaging Sciences, School of MedicineNormal and pathologic neurobiological processes influence brain morphology in coordinated ways that give rise to patterns of structural covariance (PSC) across brain regions and individuals during brain aging and diseases. The genetic underpinnings of these patterns remain largely unknown. We apply a stochastic multivariate factorization method to a diverse population of 50,699 individuals (12 studies and 130 sites) and derive data-driven, multi-scale PSCs of regional brain size. PSCs were significantly correlated with 915 genomic loci in the discovery set, 617 of which are newly identified, and 72% were independently replicated. Key pathways influencing PSCs involve reelin signaling, apoptosis, neurogenesis, and appendage development, while pathways of breast cancer indicate potential interplays between brain metastasis and PSCs associated with neurodegeneration and dementia. Using support vector machines, multi-scale PSCs effectively derive imaging signatures of several brain diseases. Our results elucidate genetic and biological underpinnings that influence structural covariance patterns in the human brain.Item Novel rare variant associations with late‐life cognitive performance(Wiley, 2025-01-09) Regelson, Alexandra N.; Archer, Derek B.; Durant, Alaina; Mukherjee, Shubhabrata; Lee, Michael L.; Choi, Seo-Eun; Scollard, Phoebe; Trittschuh, Emily H.; Mez, Jesse; Bush, William S.; Kuzma, Amanda B.; Cuccaro, Michael L.; Cruchaga, Carlos; Farrer, Lindsay A.; Wang, Li-San; Schellenberg, Gerard D.; Mayeux, Richard; Kukull, Walter A.; Keene, C. Dirk; Saykin, Andrew J.; Johnson, Sterling C.; Engelman, Corinne D.; Bennett, David A.; Barnes, Lisa L.; Larson, Eric B.; Nho, Kwangsik; Goate, Alison M.; Renton, Alan E.; Marcora, Edoardo; Fulton-Howard, Brian; Patel, Tulsi; Risacher, Shannon L.; DeStefano, Anita L.; Schneider, Julie A.; Habes, Mohamad; Seshadri, Sudha; Satizabal, Claudia L.; Maillard, Pauline; Toga, Arthur W.; Crawford, Karen; Tosun, Duygu; Vance, Jeffery M.; Mormino, Elizabeth; DeCarli, Charles S.; Montine, Thomas J.; Beecham, Gary; Biber, Sarah A.; De Jager, Philip L.; Vardarajan, Badri N.; Lee, Annie J.; Brickman, Adam M.; Reitz, Christiane; Manly, Jennifer J.; Lu, Qiongshi; Rentería, Miguel Arce; Deming, Yuetiva; Pericak-Vance, Margaret A.; Haines, Jonathan L.; Crane, Paul K.; Hohman, Timothy J.; Dumitrescu, Logan C.; Medical and Molecular Genetics, School of MedicineBackground: Despite evidence that Alzheimer’s disease (AD) is highly heritable, there remains substantial “missing” heritability, likely due in part to the effect of rare variants and to the past reliance on case‐control analysis. Here, we leverage powerful endophenotypes of AD (cognitive performance across multiple cognitive domains) in a rare variant analysis to identify novel genetic drivers of cognition in aging and disease. Method: We leveraged 8 cohorts of cognitive aging with whole genome sequencing data from the AD Sequencing Project to conduct rare variant analyses of multiple domains of cognition (N = 9,317; mean age = 73; 56% female; 52% cognitively unimpaired). Harmonized scores for memory, executive function, and language were derived using confirmatory factor analysis models. Participants genetically similar to the 1000Genomes EUR reference panel were included in analysis. Variants included in the analysis had a minor allele frequency < 0.01, a minor allele count of ≥ 10, and were annotated as a high or moderate impact SNP using VEP. Associations of baseline scores in each cognitive domain were performed using SKAT‐O, including 92,905 rare variants among 16,243 genes. All tests were adjusted for sex, baseline age, sequencing center and platform, and genetic principal components. Correction for multiple comparisons was completed using the Benjamini‐Hochberg false discovery rate (FDR) procedure. Result: APOE was associated with baseline memory, language, and executive function, though only memory survived multiple‐test correction (p.FDR = 0.001). Outside of APOE, ITPKB was associated with baseline executive function (p.FDR = 0.048). AKTIP, SHCBP1L, and CCNF showed nominal associations with multiple domains of cognition that did not survive correction for multiple comparisons (p.FDRs<0.07). Conclusion: These results highlight novel rare variants associated with cognition. IPTKB is an AGORA nominated gene target for potential AD treatment. It is important in the regulation of immune cells and displays higher expression in the cortex of AD patients compared to controls. CCNF and AKTIP are brain eQTLs and have differential RNA expression in AD brains. Previously, variants in AKTIP have been associated with educational attainment, intelligence, and memory, while variants in CCNF have been associated with neuritic plaques and neurofibrillary tangles. Future analyses will incorporate longitudinal cognition and expand into additional populations.Item Sex and APOE ε4 allele differences in longitudinal white matter microstructure in multiple cohorts of aging and Alzheimer's disease(Wiley, 2025) Peterson, Amalia; Sathe, Aditi; Zaras, Dimitrios; Yang, Yisu; Durant, Alaina; Deters, Kacie D.; Shashikumar, Niranjana; Pechman, Kimberly R.; Kim, Michael E.; Gao, Chenyu; Khairi, Nazirah Mohd; Li, Zhiyuan; Yao, Tianyuan; Huo, Yuankai; Dumitrescu, Logan; Gifford, Katherine A.; Wilson, Jo Ellen; Cambronero, Francis E.; Risacher, Shannon L.; Beason-Held, Lori L.; An, Yang; Arfanakis, Konstantinos; Erus, Guray; Davatzikos, Christos; Tosun, Duygu; Toga, Arthur W.; Thompson, Paul M.; Mormino, Elizabeth C.; Habes, Mohamad; Wang, Di; Zhang, Panpan; Schilling, Kurt; Alzheimer's Disease Neuroimaging Initiative (ADNI); BIOCARD Study Team; Alzheimer's Disease Sequencing Project (ADSP); Albert, Marilyn; Kukull, Walter; Biber, Sarah A.; Landman, Bennett A.; Johnson, Sterling C.; Schneider, Julie; Barnes, Lisa L.; Bennett, David A.; Jefferson, Angela L.; Resnick, Susan M.; Saykin, Andrew J.; Hohman, Timothy J.; Archer, Derek B.; Radiology and Imaging Sciences, School of MedicineIntroduction: The effects of sex and apolipoprotein E (APOE)-Alzheimer's disease (AD) risk factors-on white matter microstructure are not well characterized. Methods: Diffusion magnetic resonance imaging data from nine well-established longitudinal cohorts of aging were free water (FW)-corrected and harmonized. This dataset included 4741 participants (age = 73.06 ± 9.75) with 9671 imaging sessions over time. FW and FW-corrected fractional anisotropy (FAFWcorr) were used to assess differences in white matter microstructure by sex and APOE ε4 carrier status. Results: Sex differences in FAFWcorr in projection tracts and APOE ε4 differences in FW limbic and occipital transcallosal tracts were most pronounced. Discussion: There are prominent differences in white matter microstructure by sex and APOE ε4 carrier status. This work adds to our understanding of disparities in AD. Additional work to understand the etiology of these differences is warranted. Highlights: Sex and apolipoprotein E (APOE) ε4 carrier status relate to white matter microstructural integrity. Females generally have lower free water-corrected fractional anisotropy compared to males. APOE ε4 carriers tended to have higher free water than non-carriers.Item The effect of Alzheimer's disease genetic factors on limbic white matter microstructure(Wiley, 2025) Lorenz, Anna; Sathe, Aditi; Zaras, Dimitrios; Yang, Yisu; Durant, Alaina; Kim, Michael E.; Gao, Chenyu; Newlin, Nancy R.; Ramadass, Karthik; Kanakaraj, Praitayini; Khairi, Nazirah Mohd; Li, Zhiyuan; Yao, Tianyuan; Huo, Yuankai; Dumitrescu, Logan; Shashikumar, Niranjana; Pechman, Kimberly R.; Jackson, Trevor Bryan; Workmeister, Abigail W.; Risacher, Shannon L.; Beason-Held, Lori L.; An, Yang; Arfanakis, Konstantinos; Erus, Guray; Davatzikos, Christos; Habes, Mohamad; Wang, Di; Tosun, Duygu; Toga, Arthur W.; Thompson, Paul M.; Mormino, Elizabeth C.; Zhang, Panpan; Schilling, Kurt; Alzheimer's Disease Neuroimaging Initiative (ADNI)The BIOCARD Study Team; The Alzheimer's Disease Sequencing Project (ADSP); Albert, Marilyn; Kukull, Walter; Biber, Sarah A.; Landman, Bennett A.; Johnson, Sterling C.; Bendlin, Barbara; Schneider, Julie; Barnes, Lisa L.; Bennett, David A.; Jefferson, Angela L.; Resnick, Susan M.; Saykin, Andrew J.; Hohman, Timothy J.; Archer, Derek B.; Radiology and Imaging Sciences, School of MedicineIntroduction: White matter (WM) microstructure is essential for brain function but deteriorates with age and in neurodegenerative conditions such as Alzheimer's disease (AD). Diffusion MRI, enhanced by advanced bi-tensor models accounting for free water (FW), enables in vivo quantification of WM microstructural differences. Methods: To evaluate how AD genetic risk factors affect limbic WM microstructure - crucial for memory and early impacted in disease - we conducted linear regression analyses in a cohort of 2,614 non-Hispanic White aging adults (aged 50.12 to 100.85 years). The study evaluated 36 AD risk variants across 26 genes, the association between AD polygenic scores (PGSs) and WM metrics, and interactions with cognitive status. Results: AD PGSs, variants in TMEM106B, PTK2B, WNT3, and apolipoprotein E (APOE), and interactions involving MS4A6A were significantly linked to WM microstructure. Discussion: These findings implicate AD-related genetic factors related to neurodevelopment (WNT3), lipid metabolism (APOE), and inflammation (TMEM106B, PTK2B, MS4A6A) that contribute to alternations in WM microstructure in older adults. Highlights: AD risk variants in TMEM106B, PTK2B, WNT3, and APOE genes showed distinct associations with limbic FW-corrected WM microstructure metrics. Interaction effects were observed between MS4A6A variants and cognitive status. PGS for AD was associated with higher FW content in the limbic system.