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Publications
| Title | Journal | Year | Authors | Volume | Issue | Pages | Abstract | Link | PMC |
|---|---|---|---|---|---|---|---|---|---|
| Title | Journal | Year | Authors | Volume | Issue | Pages | Abstract | Link | PMC |
| A deep neural network estimation of brain age is sensitive to cognitive impairment and decline | Pacific Symposium on Biocomputing | 2024 | Yang, Y., Sathe, A., Schilling, K., Shashikumar, N., Moore, E., Dumitrescu, L., Pechman, K. R., Landman, B. A., Gifford, K. A., Hohman, T. J., Jefferson, A. L., & Archer, D. B. | 29 | 148-162 | "The greatest known risk factor for Alzheimer's disease (AD) is age. While both normal aging and AD pathology involve structural changes in the brain, their trajectories of atrophy are not the same. Recent developments in artificial intelligence have encouraged studies to leverage neuroimaging-derived measures and deep learning approaches to predict brain age, which has shown promise as a sensitive biomarker in diagnosing and monitoring AD. However, prior efforts primarily involved structural magnetic resonance imaging and conventional diffusion MRI (dMRI) metrics without accounting for partial volume effects. To address this issue, we post-processed our dMRI scans with an advanced free-water (FW) correction technique to compute distinct FW-corrected fractional anisotropy (FAFWcorr) and FW maps that allow for the separation of tissue from fluid in a scan. We built 3 densely connected neural networks from FW-corrected dMRI, T1-weighted MRI, and combined FW+T1 features, respectively, to predict brain age. We then investigated the relationship of actual age and predicted brain ages with cognition. We found that all models accurately predicted actual age in cognitively unimpaired (CU) controls (FW: r=0.66, p=1.62x10-32; T1: r=0.61, p=1.45x10-26, FW+T1: r=0.77, p=6.48x10-50) and distinguished between CU and mild cognitive impairment participants (FW: p=0.006; T1: p=0.048; FW+T1: p=0.003), with FW+T1-derived age showing best performance. Additionally, all predicted brain age models were significantly associated with cross-sectional cognition (memory, FW: _=-1.094, p=6.32x10-7; T1: _=-1.331, p=6.52x10-7; FW+T1: _=-1.476, p=2.53x10-10; executive function, FW: _=-1.276, p=1.46x10-9; T1: _=-1.337, p=2.52x10-7; FW+T1: _=-1.850, p=3.85x10-17) and longitudinal cognition (memory, FW: _=-0.091, p=4.62x10-11; T1: _=-0.097, p=1.40x10-8; FW+T1: _=-0.101, p=1.35x10-11; executive function, FW: _=-0.125, p=1.20x10-10; T1: _=-0.163, p=4.25x10-12; FW+T1: _=-0.158, p=1.65x10-14). Our findings provide evidence that both T1-weighted MRI and dMRI measures improve brain age prediction and support predicted brain age as a sensitive biomarker of cognition and cognitive decline." | PubMed Link | PMC10764074 | |
| A genome-wide search for pleiotropy in more than 100,000 harmonized longitudinal cognitive domain scores | Molecular Neurodegeneration | 2023 | Kang, M., Ang, T. F. A., Devine, S. A., Sherva, R., Mukherjee, S., Trittschuh, E. H., Gibbons, L. E., Scollard, P., Lee, M., Choi, S.-E., Klinedinst, B., Nakano, C., Dumitrescu, L. C., Durant, A., Hohman, T. J., Cuccaro, M. L., Saykin, A. J., Kukull, W. A., Bennett, D. A., & Farrer, L. A. | 18 | 1 | 40 | "Background: More than 75 common variant loci account for only a portion of the heritability for Alzheimer's disease (AD). A more complete understanding of the genetic basis of AD can be deduced by exploring associations with AD-related endophenotypes. Methods: We conducted genome-wide scans for cognitive domain performance using harmonized and co-calibrated scores derived by confirmatory factor analyses for executive function, language, and memory. We analyzed 103,796 longitudinal observations from 23,066 members of community-based (FHS, ACT, and ROSMAP) and clinic-based (ADRCs and ADNI) cohorts using generalized linear mixed models including terms for SNP, age, SNP _ age interaction, sex, education, and five ancestry principal components. Significance was determined based on a joint test of the SNP's main effect and interaction with age. Results across datasets were combined using inverse-variance meta-analysis. Genome-wide tests of pleiotropy for each domain pair as the outcome were performed using PLACO software. Results: Individual domain and pleiotropy analyses revealed genome-wide significant (GWS) associations with five established loci for AD and AD-related disorders (BIN1, CR1, GRN, MS4A6A, and APOE) and eight novel loci. ULK2 was associated with executive function in the community-based cohorts (rs157405, P = 2.19 _ 10-9). GWS associations for language were identified with CDK14 in the clinic-based cohorts (rs705353, P = 1.73 _ 10-8) and LINC02712 in the total sample (rs145012974, P = 3.66 _ 10-8). GRN (rs5848, P = 4.21 _ 10-8) and PURG (rs117523305, P = 1.73 _ 10-8) were associated with memory in the total and community-based cohorts, respectively. GWS pleiotropy was observed for language and memory with LOC107984373 (rs73005629, P = 3.12 _ 10-8) in the clinic-based cohorts, and with NCALD (rs56162098, P = 1.23 _ 10-9) and PTPRD (rs145989094, P = 8.34 _ 10-9) in the community-based cohorts. GWS pleiotropy was also found for executive function and memory with OSGIN1 (rs12447050, P = 4.09 _ 10-8) and PTPRD (rs145989094, P = 3.85 _ 10-8) in the community-based cohorts. Functional studies have previously linked AD to ULK2, NCALD, and PTPRD. Conclusion: Our results provide some insight into biological pathways underlying processes leading to domain-specific cognitive impairment and AD, as well as a conduit toward a syndrome-specific precision medicine approach to AD. Increasing the number of participants with harmonized cognitive domain scores will enhance the discovery of additional genetic factors of cognitive decline leading to AD and related dementias. " | PubMed Link | PMC10286470 |
| Alzheimer's Disease Genetic Risk, Cognition, and Brain Aging in Midlife | Annals of Neurology | 2023 | Brenowitz, W. D., Fornage, M., Launer, L. J., Habes, M., Davatzikos, C., & Yaffe, K. | 93 | 3 | 629-634 | We examined associations of an Alzheimer's disease (AD) Genetic Risk Score (AD-GRS) and midlife cognitive and neuroimaging outcomes in 1,252 middle-aged participants (311 with brain MRI). A higher AD-GRS based on 25 previously identified loci (excluding apolipoprotein E [APOE]) was associated with worse Montreal Cognitive Assessment (-0.14 standard deviation [SD] [95% confidence interval {CI}: -0.26, -0.02]), older machine learning predicted brain age (2.35 years[95%CI: 0.01, 4.69]), and white matter hyperintensity volume (0.35 SD [95% CI: 0.00, 0.71]), but not with a composite cognitive outcome, total brain, or hippocampal volume. APOE _4 allele was not associated with any outcomes. AD risk genes beyond APOE may contribute to subclinical differences in cognition and brain health in midlife. ANN NEUROL 2023;93:629-634. | PubMed Link | PMC9974745 |
| APOE effects on regional tau in preclinical Alzheimer's disease | Molecular neurodegeneration | 2023 | Young, C. B., Johns, E., Kennedy, G., Belloy, M. E., Insel, P. S., Greicius, M. D., Sperling, R. A., Johnson, K. A., Poston, K. L., Mormino, E. C., AlzheimerÕs Disease Neuroimaging Initiative, & A4 Study Team. | 18 | 1 | 1 | "Background: APOE variants are strongly associated with abnormal amyloid aggregation and additional direct effects of APOE on tau aggregation are reported in animal and human cell models. The degree to which these effects are present in humans when individuals are clinically unimpaired (CU) but have abnormal amyloid (A_+) remains unclear. Methods: We analyzed data from CU individuals in the Anti-Amyloid Treatment in Asymptomatic AD (A4) and Longitudinal Evaluation of Amyloid Risk and Neurodegeneration (LEARN) studies. Amyloid PET data were available for 4486 participants (3163 A_-, 1323 A_+) and tau PET data were available for a subset of 447 participants (55 A_-, 392 A_+). Linear models examined APOE (number of e2 and e4 alleles) associations with global amyloid and regional tau burden in medial temporal lobe (entorhinal, amygdala) and early neocortical regions (inferior temporal, inferior parietal, precuneus). Consistency of APOE4 effects on regional tau were examined in 220 A_ + CU and mild cognitive impairment (MCI) participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Results: APOE2 and APOE4 were associated with lower and higher amyloid positivity rates, respectively. Among A_+ CU, e2 and e4 were associated with reduced (-12 centiloids per allele) and greater (+15 centiloids per allele) continuous amyloid burden, respectively. APOE2 was associated with reduced regional tau in all regions (-0.05 to -0.09 SUVR per allele), whereas APOE4 was associated with greater regional tau (+0.02 to +0.07 SUVR per allele). APOE differences were confirmed by contrasting e3/e3 with e2/e3 and e3/e4. Mediation analyses among A_+ s showed that direct effects of e2 on regional tau were present in medial temporal lobe and early neocortical regions, beyond an indirect pathway mediated by continuous amyloid burden. For e4, direct effects on regional tau were only significant in medial temporal lobe. The magnitude of protective e2 effects on regional tau was consistent across brain regions, whereas detrimental e4 effects were greatest in medial temporal lobe. APOE4 patterns were confirmed in A_+ ADNI participants. Conclusions: APOE influences early regional tau PET burden, above and beyond effects related to cross-sectional amyloid PET burden. Therapeutic strategies targeting underlying mechanisms related to APOE may modify tau accumulation among A_+ individuals." | PubMed Link | PMC9811772 |
| APOE loss-of-function variants: Compatible with longevity and associated with resistance to Alzheimer's Disease pathology | Neuron | 2024 | Chemparathy, A., Le Guen, Y., Chen, S., Lee, E. G., Leong, L., Gorzynski, J.E., Jensen, T. D., Ferrasse, A., Xu, G., Xiang, H., Belloy, M. E., Kasireddy, N., Pe-Tauber, A., Williams, K., Stewart, I., Talozzi, L., Wingo, T. S., Lah, J. J., Jayadev, S., Hales, C. M., Peskind, E., Child, D. D., Roeber, S., Keene, C. D., Cong, L., Ashley, E. A., Yu, C. E., & Greicius, M. D. | 112 | 7 | 1110-1116.e5 | "The _4 allele of apolipoprotein E (APOE) is the strongest genetic risk factor for sporadic Alzheimer's disease (AD). Knockdown of _4 may provide a therapeutic strategy for AD, but the effect of APOE loss of function (LoF) on AD pathogenesis is unknown. We searched for APOE LoF variants in a large cohort of controls and patients with AD and identified seven heterozygote carriers of APOE LoF variants. Five carriers were controls (aged 71-90 years), one carrier was affected by progressive supranuclear palsy, and one carrier was affected by AD with an unremarkable age at onset of 75 years. Two APOE _3/_4 controls carried a stop-gain affecting _4: one was cognitively normal at 90 years and had no neuritic plaques at autopsy; the other was cognitively healthy at 79 years, and lumbar puncture at 76 years showed normal levels of amyloid. These results suggest that _4 drives AD risk through the gain of abnormal function and support _4 knockdown as a viable therapeutic option." | PubMed Link | PMC10402217 |
| Assessment of Risk Factors and Clinical Importance of Enlarged Perivascular Spaces by Whole-Brain Investigation in the Multi-Ethnic Study of Atherosclerosis. | JAMA Network Open | 2023 | Charisis, S., Rashid, T., Liu, H., Ware, J. B., Jensen, P. N., Austin, T. R., Li, K., Fadaee, E., Hilal, S., Chen, C., Hughes, T. M., Romero, J. R., Toledo, J. B., Longstreth, W. T., Hohman, T. J., Nasrallah, I., Bryan, R. N., Launer, L. J., Davatzikos, C., & Habes, M. | 6 | 4 | e239196 | "Importance: Enlarged perivascular spaces (ePVSs) have been associated with cerebral small-vessel disease (cSVD). Although their etiology may differ based on brain location, study of ePVSs has been limited to specific brain regions; therefore, their risk factors and significance remain uncertain. Objective: Toperform a whole-brain investigation of ePVSs in a large community-based cohort. Design, setting, and participants: This cross-sectional study analyzed data from the Atrial Fibrillation substudy of the population-based Multi-Ethnic Study of Atherosclerosis. Demographic, vascular risk, and cardiovascular disease data were collected from September 2016 to May 2018. Brain magnetic resonance imaging was performed from March 2018 to July 2019. The reported analysis was conducted between August and October 2022. A total of 1026 participants with available brain magnetic resonance imaging data and complete information on demographic characteristics and vascular risk factors were included. Main outcomes and measures: Enlarged perivascular spaces were quantified using a fully automated deep learning algorithm. Quantified ePVS volumes were grouped into 6 anatomic locations: basal ganglia, thalamus, brainstem, frontoparietal, insular, and temporal regions, and were normalized for the respective regional volumes. The association of normalized regional ePVS volumes with demographic characteristics, vascular risk factors, neuroimaging indices, and prevalent cardiovascular disease was explored using generalized linear models. Results: In the 1026 participants, mean (SD) age was 72 (8) years; 541 (53%) of the participants were women. Basal ganglia ePVS volume was positively associated with age (_ = 3.59 _ 10-3; 95% CI, 2.80 _ 10-3 to 4.39 _ 10-3), systolic blood pressure (_ = 8.35 _ 10-4; 95% CI, 5.19 _ 10-4 to 1.15 _ 10-3), use of antihypertensives (_ = 3.29 _ 10-2; 95% CI, 1.92 _ 10-2 to 4.67 _ 10-2), and negatively associated with Black race (_ = -3.34 _ 10-2; 95% CI, -5.08 _ 10-2 to -1.59 _ 10-2). Thalamic ePVS volume was positively associated with age (_ = 5.57 _ 10-4; 95% CI, 2.19 _ 10-4 to 8.95 _ 10-4) and use of antihypertensives (_ = 1.19 _ 10-2; 95% CI, 6.02 _ 10-3 to 1.77 _ 10-2). Insular region ePVS volume was positively associated with age (_ = 1.18 _ 10-3; 95% CI, 7.98 _ 10-4 to 1.55 _ 10-3). Brainstem ePVS volume was smaller in Black than in White participants (_ = -5.34 _ 10-3; 95% CI, -8.26 _ 10-3 to -2.41 _ 10-3). Frontoparietal ePVS volume was positively associated with systolic blood pressure (_ = 1.14 _ 10-4; 95% CI, 3.38 _ 10-5 to 1.95 _ 10-4) and negatively associated with age (_ = -3.38 _ 10-4; 95% CI, -5.40 _ 10-4 to -1.36 _ 10-4). Temporal region ePVS volume was negatively associated with age (_ = -1.61 _ 10-2; 95% CI, -2.14 _ 10-2 to -1.09 _ 10-2), as well as Chinese American (_ = -2.35 _ 10-1; 95% CI, -3.83 _ 10-1 to -8.74 _ 10-2) and Hispanic ethnicities (_ = -1.73 _ 10-1; 95% CI, -2.96 _ 10-1 to -4.99 _ 10-2). Conclusions and relevance: In this cross-sectional study of ePVSs in the whole brain, increased ePVS burden in the basal ganglia and thalamus was a surrogate marker for underlying cSVD, highlighting the clinical importance of ePVSs in these locations." | PubMed Link | PMC10126873 |
| 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 Network Open | 2023 | Rashid, T., Li, K., Toledo, J. B., Nasrallah, I., Pajewski, N. M., Dolui, S., Detre, J., Wolk, D. A., Liu, H., Heckbert, S. R., Bryan, R. N., Williamson, J., Davatzikos, C., Seshadri, S., Launer, L. J., & Habes, M. | 6 | 3 | e231055 | "Importance: Little is known about the associations of strict blood pressure (BP) control with microstructural changes in small vessel disease markers. Objective: To investigate the regional associations of intensive vs standard BP control with small vessel disease biomarkers, such as white matter lesions (WMLs), fractional anisotropy (FA), mean diffusivity (MD), and cerebral blood flow (CBF). Design, setting, and participants: The Systolic Blood Pressure Intervention Trial (SPRINT) is a multicenter randomized clinical trial that compared intensive systolic BP (SBP) control (SBP target <120 mm Hg) vs standard control (SBP target <140 mm Hg) among participants aged 50 years or older with hypertension and without diabetes or a history of stroke. The study began randomization on November 8, 2010, and stopped July 1, 2016, with a follow-up duration of approximately 4 years. A total of 670 and 458 participants completed brain magnetic resonance imaging at baseline and follow-up, respectively, and comprise the cohort for this post hoc analysis. Statistical analyses for this post hoc analysis were performed between August 2020 and October 2022. Interventions: At baseline, 355 participants received intensive SBP treatment and 315 participants received standard SBP treatment. Main outcomes and measures: The main outcomes were regional changes in WMLs, FA, MD (in white matter regions of interest), and CBF (in gray matter regions of interest). Results: At baseline, 355 participants (mean [SD] age, 67.7 [8.0] years; 200 men [56.3%]) received intensive BP treatment and 315 participants (mean [SD] age, 67.0 [8.4] years; 199 men [63.2%]) received standard BP treatment. Intensive treatment was associated with smaller mean increases in WML volume compared with standard treatment (644.5 mm3 vs 1258.1 mm3). The smaller mean increases were observed specifically in the deep white matter regions of the left anterior corona radiata (intensive treatment, 30.3 mm3 [95% CI, 16.0-44.5 mm3]; standard treatment, 80.5 mm3 [95% CI, 53.8-107.2 mm3]), left tapetum (intensive treatment, 11.8 mm3 [95% CI, 4.4-19.2 mm3]; standard treatment, 27.2 mm3 [95% CI, 19.4-35.0 mm3]), left superior fronto-occipital fasciculus (intensive treatment, 3.2 mm3 [95% CI, 0.7-5.8 mm3]; standard treatment, 9.4 mm3 [95% CI, 5.5-13.4 mm3]), left posterior corona radiata (intensive treatment, 26.0 mm3 [95% CI, 12.9-39.1 mm3]; standard treatment, 52.3 mm3 [95% CI, 34.8-69.8 mm3]), left splenium of the corpus callosum (intensive treatment, 45.4 mm3 [95% CI, 25.1-65.7 mm3]; standard treatment, 83.0 mm3 [95% CI, 58.7-107.2 mm3]), left posterior thalamic radiation (intensive treatment, 53.0 mm3 [95% CI, 29.8-76.2 mm3]; standard treatment, 106.9 mm3 [95% CI, 73.4-140.3 mm3]), and right posterior thalamic radiation (intensive treatment, 49.5 mm3 [95% CI, 24.3-74.7 mm3]; standard treatment, 102.6 mm3 [95% CI, 71.0-134.2 mm3]). Conclusions and relevance: This study suggests that intensive BP treatment, compared with standard treatment, was associated with a slower increase of WMLs, improved diffusion tensor imaging, and FA and CBF changes in several brain regions that represent vulnerable areas that may benefit from more strict BP control." | PubMed Link | PMC9978954 |
| Association of spermidine plasma levels with brain aging in a population-based study | Alzheimer's & Dementia: The Journal of the Alzheimer's Association | 2023 | Wortha, S. M., Frenzel, S., Bahls, M., Habes, M., Wittfeld, K., Van der Auwera, S., BŸlow, R., Zylla, S., Friedrich, N., Nauck, M., Všlzke, H., Grabe, H. J., Schwarz, C., & Flšel, A. | 19 | 5 | 1832-1840 | "Introduction: Supplementation with spermidine may support healthy aging, but elevated spermidine tissue levels were shown to be an indicator of Alzheimer's disease (AD). Methods: Data from 659 participants (age range: 21-81 years) of the population-based Study of Health in Pomerania TREND were included. We investigated the association between spermidine plasma levels and markers of brain aging (hippocampal volume, AD score, global cortical thickness [CT], and white matter hyperintensities [WMH]). Results: Higher spermidine levels were significantly associated with lower hippocampal volume (� = -0.076; 95% confidence interval [CI]: -0.13 to -0.02; q = 0.026), higher AD score (� = 0.118; 95% CI: 0.05 to 0.19; q = 0.006), lower global CT (� = -0.104; 95% CI: -0.17 to -0.04; q = 0.014), but not WMH volume. Sensitivity analysis revealed no substantial changes after excluding participants with cancer, depression, or hemolysis. Discussion: Elevated spermidine plasma levels are associated with advanced brain aging and might serve as potential early biomarker for AD and vascular brain pathology." | PubMed Link | PMC11246659 |
| Associations of Sex, Race, and Apolipoprotein E Alleles With Multiple Domains of Cognition Among Older Adults | Jama Neurology | 2023 | Walters, S., Contreras, A. G., Eissman, J. M., Mukherjee, S., Lee, M. L., Choi, S. E., Scollard, P., Trittschuh, E. H., Mez, J. B., Bush, W. S., Kunkle, B. W., Naj, A. C., Peterson, A., Gifford, K. A., Cuccaro, M. L., Cruchaga, C., Pericak-Vance, M. A., Farrer, L. A., Wang, L. S., Haines, J. L., Jefferson, A. L., Kukull, W. A., Keene, C. D., Saykin, A. J., Thompson, P. M., Martin, E. R., Bennett, D. A., Barnes, L. L., Schneider, J. A., Crane, P. K., Hohman, T. J., Dumitrescu, L., Alzheimer's Disease Neuroimaging Initiative, Alzheimer's Disease Genetics Consortium, & Alzheimer's Disease Sequencing Project. | 80 | 9 | 929-939 | "Importance: Sex differences are established in associations between apolipoprotein E (APOE) _4 and cognitive impairment in Alzheimer disease (AD). However, it is unclear whether sex-specific cognitive consequences of APOE are consistent across races and extend to the APOE _2 allele. Objective: To investigate whether sex and race modify APOE _4 and _2 associations with cognition. Design, setting, and participants: This genetic association study included longitudinal cognitive data from 4 AD and cognitive aging cohorts. Participants were older than 60 years and self-identified as non-Hispanic White or non-Hispanic Black (hereafter, White and Black). Data were previously collected across multiple US locations from 1994 to 2018. Secondary analyses began December 2021 and ended September 2022. Main outcomes and measures: Harmonized composite scores for memory, executive function, and language were generated using psychometric approaches. Linear regression assessed interactions between APOE _4 or APOE _2 and sex on baseline cognitive scores, while linear mixed-effect models assessed interactions on cognitive trajectories. The intersectional effect of race was modeled using an APOE _ sex _ race interaction term, assessing whether APOE _ sex interactions differed by race. Models were adjusted for age at baseline and corrected for multiple comparisons. Results: Of 32 427 participants who met inclusion criteria, there were 19 007 females (59%), 4453 Black individuals (14%), and 27 974 White individuals (86%); the mean (SD) age at baseline was 74 years (7.9). At baseline, 6048 individuals (19%) had AD, 4398 (14%) were APOE _2 carriers, and 12 538 (38%) were APOE _4 carriers. Participants missing APOE status were excluded (n = 9266). For APOE _4, a robust sex interaction was observed on baseline memory (_ = -0.071, SE = 0.014; P = 9.6 _ 10-7), whereby the APOE _4 negative effect was stronger in females compared with males and did not significantly differ among races. Contrastingly, despite the large sample size, no APOE _2 _ sex interactions on cognition were observed among all participants. When testing for intersectional effects of sex, APOE _2, and race, an interaction was revealed on baseline executive function among individuals who were cognitively unimpaired (_ = -0.165, SE = 0.066; P = .01), whereby the APOE _2 protective effect was female-specific among White individuals but male-specific among Black individuals. Conclusions and relevance: In this study, while race did not modify sex differences in APOE _4, the APOE _2 protective effect could vary by race and sex. Although female sex enhanced _4-associated risk, there was no comparable sex difference in _2, suggesting biological pathways underlying _4-associated risk are distinct from _2 and likely intersect with age-related changes in sex biology." | PubMed Link | PMC10352930 |
| Characterizing patterns of DTI variance in aging brains | medRxiv | 2024 | Gao, C., Yang, Q., Kim, M. E., Khairi, N. M., Cai, L. Y., Newlin, N. R., Kanakaraj, P., Remedios, L. W., Krishnan, A. R., Yu, X., Yao, T., Zhang, P., Schilling, K. G., Moyer, D., Archer, D. B., Resnick, S. M., & Landman, B. A. | "Background: As large analyses merge data across sites, a deeper understanding of variance in statistical assessment across the sources of data becomes critical for valid analyses. Diffusion tensor imaging (DTI) exhibits spatially varying and correlated noise, so care must be taken with distributional assumptions. Purpose: We characterize the role of physiology, subject compliance, and the interaction of subject with the scanner in the understanding of DTI variability, as modeled in spatial variance of derived metrics in homogeneous regions. Methods: We analyze DTI data from 1035 subjects in the Baltimore Longitudinal Study of Aging (BLSA), with ages ranging from 22.4 to 103 years old. For each subject, up to 12 longitudinal sessions were conducted. We assess variance of DTI scalars within regions of interest (ROIs) defined by four segmentation methods and investigate the relationships between the variance and covariates, including baseline age, time from the baseline (referred to as ÒintervalÓ), motion, sex, and whether it is the first scan or the second scan in the session. Results: Covariate effects are heterogeneous and bilaterally symmetric across ROIs. Inter-session interval is positively related (p _ 0.001) to FA variance in the cuneus and occipital gyrus, but negatively (p _ 0.001) in the caudate nucleus. Males show significantly (p _ 0.001) higher FA variance in the right putamen, thalamus, body of the corpus callosum, and cingulate gyrus. In 62 out of 176 ROIs defined by the Eve type-1 atlas, an increase in motion is associated (p < 0.05) with a decrease in FA variance. Head motion increases during the rescan of DTI (__ = 0.045 millimeters per volume). Conclusions: The effects of each covariate on DTI variance, and their relationships across ROIs are complex. Ultimately, we encourage researchers to include estimates of variance when sharing data and consider models of heteroscedasticity in analysis. This work provides a foundation for study planning to account for regional variations in metric variance." | PubMed Link | PMC10473788 | |||
| Cognitive domain harmonization and cocalibration in studies of older adults. | Neuropsychology | 2023 | Mukherjee, S., Choi, S. E., Lee, M. L., Scollard, P., Trittschuh, E. H., Mez, J., Saykin, A. J., Gibbons, L. E., Sanders, R. E., Zaman, A. F., Teylan, M. A., Kukull, W. A., Barnes, L. L., Bennett, D. A., Lacroix, A. Z., Larson, E. B., Cuccaro, M., Mercado, S., Dumitrescu, L., & Crane, P. K. | 37 | 4 | 409-423 | "Objective: Studies use different instruments to measure cognitirating cognitive tests permit direct comparisons of individuals across studies and pooling data for joint analyses. Method: We began our legacy item bank with data from the Adult Changes in Thought study (n = 5,546), the Alzheimer's Disease Neuroimaging Initiative (n = 3,016), the Rush Memory and Aging Project (n = 2,163), and the Religious on such as the Mini-Mental State Examination, the Alzheimer's Disease Assessment Scale-Cognitive Subscale, the Wechsler Memory Scale, and the Boston Naming Test. CocalibOrders Study (n = 1,456). Our workflow begins with categorizing items administered in each study as indicators of memory, executive functioning, language, visuospatial functioning, or none of these domains. We use confirmatory factor analysis models with data from the most recent visit on the pooled sample across these four studies for cocalibration and derive item parameters for all items. Using these item parameters, we then estimate factor scores along with corresponding standard errors for each domain for each study. We added additional studies to our pipeline as available and focused on thorough consideration of candidate anchor items with identical content and administration methods across studies. Results: Prestatistical harmonization steps such qualitative and quantitative assessment of granular cognitive items and evaluating factor structure are important steps when trying to cocalibrate cognitive scores across studies. We have cocalibrated cognitive data and derived scores for four domains for 76,723 individuals across 10 studies. Conclusions: We have implemented a large-scale effort to harmonize and cocalibrate cognitive domain scores across multiple studies of cognitive aging. Scores on the same metric facilitate meta-analyses of cognitive outcomes across studies or the joint analysis of individual data across studies. Our systematic approach allows for cocalibration of additional studies as they become available and our growing item bank enables robust investigation of cognition in the context of aging and dementia. (PsycInfo Database Record (c) 2023 APA, all rights reserved)." | PubMed Link | PMC9898463 |
| Deep Learning Based Detection of Enlarged Perivascular Spaces on Brain MRI. | Neuroimage. Reports | 2023 | Rashid, T., Liu, H., Ware, J. B., Li, K., Romero, J. R., Fadaee, E., Nasrallah, I. M., Hilal, S., Bryan, R. N., Hughes, T. M., Davatzikos, C., Launer, L., Seshadri, S., Heckbert, S. R., & Habes, M. | 3 | 1 | 100162 | "Deep learning has been demonstrated effective in many neuroimaging applications. However, in many scenarios, the number of imaging sequences capturing information related to small vessel disease lesions is insufficient to support data-driven techniques. Additionally, cohort-based studies may not always have the optimal or essential imaging sequences for accurate lesion detection. Therefore, it is necessary to determine which imaging sequences are crucial for precise detection. This study introduces a deep learning framework to detect enlarged perivascular spaces (ePVS) and aims to find the optimal combination of MRI sequences for deep learning-based quantification. We implemented an effective lightweight U-Net adapted for ePVS detection and comprehensively investigated different combinations of information from SWI, FLAIR, T1-weighted (T1w), and T2-weighted (T2w) MRI sequences. The experimental results showed that T2w MRI is the most important for accurate ePVS detection, and the incorporation of SWI, FLAIR and T1w MRI in the deep neural network had minor improvements in accuracy and resulted in the highest sensitivity and precision (sensitivity =0.82, precision =0.83). The proposed method achieved comparable accuracy at a minimal time cost compared to manual reading. The proposed automated pipeline enables robust and time-efficient readings of ePVS from MR scans and demonstrates the importance of T2w MRI for ePVS detection and the potential benefits of using multimodal images. Furthermore, the model provides whole-brain maps of ePVS, enabling a better understanding of their clinical correlates compared to the clinical rating methods within only a couple of brain regions." | PubMed Link | PMC10078801 |
| Deep neural network heatmaps capture Alzheimer�s disease patterns reported in a large meta-analysis of neuroimaging studies. | NeuroImage | 2023 | Wang, D., Honnorat, N., Fox, P. T., Ritter, K., Eickhoff, S. B., Seshadri, S., Alzheimer's Disease Neuroimaging Initiative, & Habes, M. | 269 | 119929 | "Deep neural networks currently provide the most advanced and accurate machine learning models to distinguish between structural MRI scans of subjects with Alzheimer's disease and healthy controls. Unfortunately, the subtle brain alterations captured by these models are difficult to interpret because of the complexity of these multi-layer and non-linear models. Several heatmap methods have been proposed to address this issue and analyze the imaging patterns extracted from the deep neural networks, but no quantitative comparison between these methods has been carried out so far. In this work, we explore these questions by deriving heatmaps from Convolutional Neural Networks (CNN) trained using T1 MRI scans of the ADNI data set and by comparing these heatmaps with brain maps corresponding to Support Vector Machine (SVM) activation patterns. Three prominent heatmap methods are studied: Layer-wise Relevance Propagation (LRP), Integrated Gradients (IG), and Guided Grad-CAM (GGC). Contrary to prior studies where the quality of heatmaps was visually or qualitatively assessed, we obtained precise quantitative measures by computing overlap with a ground-truth map from a large meta-analysis that combined 77 voxel-based morphometry (VBM) studies independently from ADNI. Our results indicate that all three heatmap methods were able to capture brain regions covering the meta-analysis map and achieved better results than SVM activation patterns. Among them, IG produced the heatmaps with the best overlap with the independent meta-analysis. " | PubMed Link | PMC11155416 | |
| DeepN4: Learning N4ITK Bias Field Correction for T1-weighted Images | Neuroinformatic | 2024 | Kanakaraj, P., Yao, T., Cai, L.Y., Lee, H. H., Newlin, N. R., Kim, M. E., Gao, C., Pechman, K. R., Archer, D., Hohman, T., Jefferson, A., Beason-Held, L. L., Resnick, S. M.; AlzheimerÕs Disease Neuroimaging Initiative (ADNI), BIOCARD Study Team, Garyfallidis, E., Anderson, A., Schilling, K. G., Landman, B. A., & Moyer, D. | 22 | 2 | 193-205 | "T1-weighted (T1w) MRI has low frequency intensity artifacts due to magnetic field inhomogeneities. Removal of these biases in T1w MRI images is a critical preprocessing step to ensure spatially consistent image interpretation. N4ITK bias field correction, the current state-of-the-art, is implemented in such a way that makes it difficult to port between different pipelines and workflows, thus making it hard to reimplement and reproduce results across local, cloud, and edge platforms. Moreover, N4ITK is opaque to optimization before and after its application, meaning that methodological development must work around the inhomogeneity correction step. Given the importance of bias fields correction in structural preprocessing and flexible implementation, we pursue a deep learning approximation / reinterpretation of the N4ITK bias fields correction to create a method which is portable, flexible, and fully differentiable. In this paper, we trained a deep learning network "DeepN4" on eight independent cohorts from 72 different scanners and age ranges with N4ITK-corrected T1w MRI and bias field for supervision in log space. We found that we can closely approximate N4ITK bias fields correction with na•ve networks. We evaluate the peak signal to noise ratio (PSNR) in test dataset against the N4ITK corrected images. The median PSNR of corrected images between N4ITK and DeepN4 was 47.96 dB. In addition, we assess the DeepN4 model on eight additional external datasets and show the generalizability of the approach. This study establishes that incompatible N4ITK preprocessing steps can be closely approximated by na•ve deep neural networks, facilitating more flexibility. All code and models are released at https://github.com/MASILab/DeepN4." | PubMed Link | PMC11182041 |
| Determinants of Perivascular Spaces in the General Population: A Pooled Cohort Analysis of Individual Participant Data. | Neurology | 2023 | Evans, T. E., Knol, M. J., Schwingenschuh, P., Wittfeld, K., Hilal, S., Ikram, M. A., Dubost, F., van Wijnen, K. M. H., Katschnig, P., Yilmaz, P., de Bruijne, M., Habes, M., Chen, C., Langer, S., Všlzke, H., Ikram, M. K., Grabe, H. J., Schmidt, R., Adams, H. H. H., & Vernooij, M. W. | 100 | 2 | e107-e122 | "Background and objectives: Perivascular spaces (PVS) are emerging markers of cerebral small vessel disease (CSVD), but research on their determinants has been hampered by conflicting results from small single studies using heterogeneous rating methods. In this study, we therefore aimed to identify determinants of PVS burden in a pooled analysis of multiple cohort studies using 1 harmonized PVS rating method. Methods: Individuals from 10 population-based cohort studies with adult participants from the Uniform Neuro-Imaging of Virchow-Robin Spaces Enlargement consortium and the UK Biobank were included. On MRI scans, we counted PVS in 4 brain regions (mesencephalon, hippocampus, basal ganglia, and centrum semiovale) according to a uniform and validated rating protocol, both manually and automated using a deep learning algorithm. As potential determinants, we considered demographics, cardiovascular risk factors, APOE genotypes, and other imaging markers of CSVD. Negative binomial regression models were used to examine the association between these determinants and PVS counts. Results: In total, 39,976 individuals were included (age range 20-96 years). The average count of PVS in the 4 regions increased from the age 20 years (0-1 PVS) to 90 years (2-7 PVS). Men had more mesencephalic PVS (OR [95% CI] = 1.13 [1.08-1.18] compared with women), but less hippocampal PVS (0.82 [0.81-0.83]). Higher blood pressure, particularly diastolic pressure, was associated with more PVS in all regions (ORs between 1.04-1.05). Hippocampal PVS showed higher counts with higher high-density lipoprotein cholesterol levels (1.02 [1.01-1.02]), glucose levels (1.02 [1.01-1.03]), and APOE _4-alleles (1.02 [1.01-1.04]). Furthermore, white matter hyperintensity volume and presence of lacunes were associated with PVS in multiple regions, but most strongly with the basal ganglia (1.13 [1.12-1.14] and 1.10 [1.09-1.12], respectively). Discussion: Various factors are associated with the burden of PVS, in part regionally specific, which points toward a multifactorial origin beyond what can be expected from PVS-related risk factor profiles. This study highlights the power of collaborative efforts in population neuroimaging research." | PubMed Link | PMC9841448 |
| DNA from multiple viral species is associated with Alzheimer's disease risk. | Alzheimer's & dementia : the journal of the Alzheimer's Association | 2024 | Tejeda, M., Farrell, J., Zhu, C., Wetzler, L., Lunetta, K. L., Bush, W.S., Martin, E. R., Wang, L. S., Schellenberg, G. D., Pericak-Vance, M. A., Haines, J. L., Farrer, L. A., & Sherva, R. | 20 | 1 | 253-265 | "Introduction: Multiple infectious agents, including viruses, bacteria, fungi, and protozoa, have been linked to Alzheimer's disease (AD) risk by independent lines of evidence. We explored this association by comparing the frequencies of viral species identified in a large sample of AD cases and controls. Methods: DNA sequence reads that did not align to the human genome in sequences were mapped to viral reference sequences, quantified, and then were tested for association with AD in whole exome sequences (WES) and whole genome sequences (WGS) datasets. Results: Several viruses were significant predictors of AD according to the machine learning classifiers. Subsequent regression analyses showed that herpes simplex type 1 (HSV-1) (odds ratio [OR] = 3.71, p = 8.03 _ 10-4) and human papillomavirus 71 (HPV-71; OR = 3.56, p = 0.02), were significantly associated with AD after Bonferroni correction. The phylogenetic-related cluster of Herpesviridae was significantly associated with AD in several strata of the data (p < 0.01). Discussion: Our results support the hypothesis that viral infection, especially HSV-1, is associated with AD risk. " | PubMed Link | PMC10840621 |
| Five dominant dimensions of brain aging are identified via deep learning: associations with clinical, lifestyle, and genetic measures. | medRxiv | 2023 | Yang, Z., Wen, J., Erus, G., Govindarajan, S. T., Melhem, R., Mamourian, E., Cui, Y., Srinivasan, D., Abdulkadir, A., Parmpi, P., Wittfeld, K., Grabe, H. J., BŸlow, R., Frenzel, S., Tosun, D., Bilgel, M., An, Y., Yi, D., Marcus, D. S., LaMontagne, P., Benzinger, T. L. S., Heckbert, S. R., Austin, T. R., Waldstein, S. R., Evans, M. K., Zonderman, A. B., Launer, L. J., Sotiras, A., Espeland, M. A., Masters, C. L., Maruff, P., Fripp, J., Toga, A., O'Bryant, S., Chakravarty, M. M., Villeneuve, S., Johnson, S. C., Morris, J. C., Albert, M. S., Yaffe, K., Všlzke, H., Ferrucci, L., Bryan, N. R., Shinohara, R. T., Fan, Y., Habes, M., Lalousis, P. A., Koutsouleris, N., Wolk, D. A., Resnick, S. M., Shou, H., Nasrallah, I. M., & Davatzikos, C. | "Brain aging is a complex process influenced by various lifestyle, environmental, and genetic factors, as well as by age-related and often co-existing pathologies. MRI and, more recently, AI methods have been instrumental in understanding the neuroanatomical changes that occur during aging in large and diverse populations. However, the multiplicity and mutual overlap of both pathologic processes and affected brain regions make it difficult to precisely characterize the underlying neurodegenerative profile of an individual from an MRI scan. Herein, we leverage a state-of-the art deep representation learning method, Surreal-GAN, and present both methodological advances and extensive experimental results that allow us to elucidate the heterogeneity of brain aging in a large and diverse cohort of 49,482 individuals from 11 studies. Five dominant patterns of neurodegeneration were identified and quantified for each individual by their respective (herein referred to as) R-indices. Significant associations between R-indices and distinct biomedical, lifestyle, and genetic factors provide insights into the etiology of observed variances. Furthermore, baseline R-indices showed predictive value for disease progression and mortality. These five R-indices contribute to MRI-based precision diagnostics, prognostication, and may inform stratification into clinical trials. " | PubMed Link | PMC10793523 | |||
| Gene-SGAN: discovering disease subtypes with imaging and genetic signatures via multi-view weakly-supervised deep clustering. | Nature communications | 2024 | Yang, Z., Wen, J., Abdulkadir, A., Cui, Y., Erus, G., Mamourian, E., Melhem, R., Srinivasan, D., Govindarajan, S. T., Chen, J., Habes, M., Masters, C. L., Maruff, P., Fripp, J., Ferrucci, L., Albert, M. S., Johnson, S. C., Morris, J. C., LaMontagne, P., Marcus, D. S., Benzinger, T. L. S., Wolk, D. A., Shen, L., Bao, J., Resnick, S. M., Shou, H., Nasrallah, I. M., & Davatzikos, C. | 15 | 1 | 354 | "Disease heterogeneity has been a critical challenge for precision diagnosis and treatment, especially in neurologic and neuropsychiatric diseases. Many diseases can display multiple distinct brain phenotypes across individuals, potentially reflecting disease subtypes that can be captured using MRI and machine learning methods. However, biological interpretability and treatment relevance are limited if the derived subtypes are not associated with genetic drivers or susceptibility factors. Herein, we describe Gene-SGAN - a multi-view, weakly-supervised deep clustering method - which dissects disease heterogeneity by jointly considering phenotypic and genetic data, thereby conferring genetic correlations to the disease subtypes and associated endophenotypic signatures. We first validate the generalizability, interpretability, and robustness of Gene-SGAN in semi-synthetic experiments. We then demonstrate its application to real multi-site datasets from 28,858 individuals, deriving subtypes of Alzheimer's disease and brain endophenotypes associated with hypertension, from MRI and single nucleotide polymorphism data. Derived brain phenotypes displayed significant differences in neuroanatomical patterns, genetic determinants, biological and clinical biomarkers, indicating potentially distinct underlying neuropathologic processes, genetic drivers, and susceptibility factors. Overall, Gene-SGAN is broadly applicable to disease subtyping and endophenotype discovery, and is herein tested on disease-related, genetically-associated neuroimaging phenotypes." | PubMed Link | PMC10774282 |
| Global Perspectives on the Management of Primary Progressive Aphasia. | Research square | 2024 | GallŽe, J., Cartwright, J., Grasso, S., Jokel, R., Lavoie, M., McGowan, E., Pozzebon, M., Beber, B. C., Duboisdindien, G., Montagut, N., Norvik, M., Sugimoto, T., Townsend, R., Unger, N., Winsnes, I. E., & Volkmer, A. | "Speech-language therapists/pathologists (SLT/Ps) are key professionals in the management and treatment of primary progressive aphasia (PPA), however, there are gaps in education and training within the discipline, with implications for skills, confidence, and clinical decision-making. This survey aimed to explore the areas of need amongst SLT/Ps working with people living with PPA (PwPPA) internationally to upskill the current and future workforce working with progressive communication disorders. One hundred eighty-five SLT/Ps from 27 countries who work with PwPPA participated in an anonymous online survey about their educational and clinical experiences, clinical decision-making, and self-reported areas of need when working with this population. Best practice principles for SLT/Ps working with PwPPA were used to frame the latter two sections of this survey. Only 40.7% of respondents indicated that their university education prepared them for their current work with PwPPA. Competency areas of "Knowing people deeply," "Practical issues," "Connectedness," and "Preventing disasters" were identified as the basic areas of priority and need. Respondents identified instructional online courses (92.5%), sample tools and activities for interventions (64.8%), and concrete training on providing care for advanced stages and end of life (58.3%) as central areas of need in their current work. This is the first international survey to comprehensively explore the perspectives of SLT/Ps working with PwPPA. Based on survey outcomes, there is a pressing need to enhance current educational and ongoing training opportunities to better promote the well-being of PwPPA and their families, and to ensure appropriate preparation of the current and future SLT/P workforce." | PubMed Link | PMC10984010 | |||
| Harmonizing the preclinical Alzheimer cognitive composite for multicohort studies. | Neuropsychology | 2023 | Hampton, O. L., Mukherjee, S., Properzi, M. J., Schultz, A. P., Crane, P. K., Gibbons, L. E., Hohman, T. J., Maruff, P., Lim, Y. Y., Amariglio, R. E., Papp, K. V., Johnson, K. A., Rentz, D. M., Sperling, R. A., & Buckley, R. F. | 37 | 4 | 436-449 | "Objectives: Studies are increasingly examining research questions across multiple cohorts using data from the preclinical Alzheimer cognitive composite (PACC). Our objective was to use modern psychometric approaches to develop a harmonized PACC. Method: We used longitudinal data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), Harvard Aging Brain Study (HABS), and Australian Imaging, Biomarker and Lifestyle Study of Ageing (AIBL) cohorts (n = 2,712). We further demonstrated our method with the Anti-Amyloid Treatment of Asymptomatic Alzheimer's Disease (A4) Study prerandomized data (n = 4,492). For the harmonization method, we used confirmatory factor analysis (CFA) on the final visit of the longitudinal cohorts to determine parameters to generate latent PACC (lPACC) scores. Overlapping tests across studies were set as ""anchors"" that tied cohorts together, while parameters from unique tests were freely estimated. We performed validation analyses to assess the performance of lPACC versus the common standardized PACC (zPACC). Results: Baseline (BL) scores for the zPACC were centered on zero, by definition. The harmonized lPACC did not define a common mean of zero and demonstrated differences in baseline ability levels across the cohorts. Baseline lPACC slightly outperformed zPACC in the prediction of progression to dementia. Longitudinal change in the lPACC was more constrained and less variable relative to the zPACC. In combined-cohort analyses, longitudinal lPACC slightly outperformed longitudinal zPACC in its association with baseline _-amyloid status. Conclusions: This study proposes procedures for harmonizing the PACC that make fewer strong assumptions than the zPACC, facilitating robust multicohort analyses. This implementation of item response theory lends itself to adapting across future cohorts with similar composites. (PsycInfo Database Record (c) 2023 APA, all rights reserved)." | PubMed Link | PMC9859944 |
| Higher performance for women than men in MRI-based Alzheimer's disease detection. | Alzheimer's Research & Therapy | 2023 | Klingenberg, M., Stark, D., Eitel, F., Budding, C., Habes, M., Ritter, K., & Alzheimer's Disease Neuroimaging Initiative. | 15 | 1 | 84 | "Introduction: Although machine learning classifiers have been frequently used to detect Alzheimer�s disease (AD) based on structural brain MRI data, potential bias with respect to sex and age has not yet been addressed. Here, we examine a state-of-the-art AD classifier for potential sex and age bias even in the case of balanced training data. Methods: Based on an age- and sex-balanced cohort of 432 subjects (306 healthy controls, 126 subjects with AD) extracted from the ADNI data base, we trained a convolutional neural network to detect AD in MRI brain scans and performed ten different random training-validation-test splits to increase robustness of the results. Classifier decisions for single subjects were explained using layer-wise relevance propagation. Results: The classifier performed significantly better for women (balanced accuracy 87.58�1.14% 87.5�1.14%) than for men (79.05�1.27% 79.05�1.27%). No significant differences were found in clinical AD scores, ruling out a disparity in disease severity as a cause for the performance difference. Analysis of the explanations revealed a larger variance in regional brain areas for male subjects compared to female subjects. Discussion: The identified sex differences cannot be attributed to an imbalanced training dataset and therefore point to the importance of examining and reporting classifier performance across population subgroups to increase transparency and algorithmic fairness. Collecting more data especially among underrepresented subgroups and balancing the dataset are important but do not always guarantee a fair outcome." | PubMed Link | PMC10116672 |
| Identifying individuals with non-Alzheimer's disease co-pathologies: A precision medicine approach to clinical trials in sporadic Alzheimer's disease | Alzheimer's & dementia : the journal of the Alzheimer's Association | 2024 | Tosun, D., Yardibi, O., Benzinger, T. L. S., Kukull, W. A., Masters, C. L., Perrin, R. J., Weiner, M. W., Simen, A., Schwarz, A. J., & Alzheimer's Disease Neuroimaging Initiative. | 20 | 1 | 421-436 | "Introduction: Biomarkers remain mostly unavailable for non-Alzheimer's disease neuropathological changes (non-ADNC) such as transactive response DNA-binding protein 43 (TDP-43) proteinopathy, Lewy body disease (LBD), and cerebral amyloid angiopathy (CAA). Methods: A multilabel non-ADNC classifier using magnetic resonance imaging (MRI) signatures was developed for TDP-43, LBD, and CAA in an autopsy-confirmed cohort (N = 214). Results: A model using demographic, genetic, clinical, MRI, and ADNC variables (amyloid positive [A_+] and tau+) in autopsy-confirmed participants showed accuracies of 84% for TDP-43, 81% for LBD, and 81% to 93% for CAA, outperforming reference models without MRI and ADNC biomarkers. In an ADNI cohort (296 cognitively unimpaired, 401 mild cognitive impairment, 188 dementia), A_ and tau explained 33% to 43% of variance in cognitive decline; imputed non-ADNC explained an additional 16% to 26%. Accounting for non-ADNC decreased the required sample size to detect a 30% effect on cognitive decline by up to 28%. Discussion: Our results lead to a better understanding of the factors that influence cognitive decline and may lead to improvements in AD clinical trial design." | PubMed Link | PMC10843695 |
| Leveraging longitudinal diffusion MRI data to quantify differences in white matter microstructural decline in normal and abnormal aging | Alzheimer's & dementia (Amsterdam, Netherlands) | 2023 | Archer, D. B., Schilling, K., Shashikumar, N., Jasodanand, V., Moore, E. E., Pechman, K. R., Bilgel, M., Beason-Held, L. L., An, Y., Shafer, A., Ferrucci, L., Risacher, S. L., Gifford, K. A., Landman, B. A., Jefferson, A. L., Saykin, A. J., Resnick, S. M., Hohman, T. J., & Alzheimer's Disease Neuroimaging Initiative. | 15 | 4 | e12468 | "Introduction: It is unclear how rates of white matter microstructural decline differ between normal aging and abnormal aging. Methods: Diffusion MRI data from several well-established longitudinal cohorts of aging (Alzheimer's Disease Neuroimaging Initiative [ADNI], Baltimore Longitudinal Study of Aging [BLSA], Vanderbilt Memory & Aging Project [VMAP]) were free-water corrected and harmonized. This dataset included 1723 participants (age at baseline: 72.8 � 8.87 years, 49.5% male) and 4605 imaging sessions (follow-up time: 2.97 � 2.09 years, follow-up range: 1-13 years, mean number of visits: 4.42 � 1.98). Differences in white matter microstructural decline in normal and abnormal agers was assessed. Results: While we found a global decline in white matter in normal/abnormal aging, we found that several white matter tracts (e.g., cingulum bundle) were vulnerable to abnormal aging. Conclusions: There is a prevalent role of white matter microstructural decline in aging, and future large-scale studies in this area may further refine our understanding of the underlying neurodegenerative processes. Highlights: Longitudinal data were free-water corrected and harmonized.Global effects of white matter decline were seen in normal and abnormal aging.The free-water metric was most vulnerable to abnormal aging.Cingulum free-water was the most vulnerable to abnormal aging." | PubMed Link | PMC10473788 |
| Longitudinal change in memory performance as a strong endophenotype for Alzheimer's disease | Alzheimer's & dementia : the journal of the Alzheimer's Association | 2024 | Archer, D. B., Eissman, J. M., Mukherjee, S., Lee, M. L., Choi, S. E., Scollard, P., Trittschuh, E. H., Mez, J. B., Bush, W. S., Kunkle, B. W., Naj, A. C., Gifford, K. A., Alzheimer's Disease Neuroimaging Initiative (ADNI), Alzheimer's Disease Genetics Consortium (ADGC), Alzheimer's Disease Sequencing Project (ADSP), Cuccaro, M. L., Pericak-Vance, M. A., Farrer, L. A., Wang, L. S., Schellenberg, G. D., Mayeux, R. P., Haines, J. L., Jefferson, A. L., Kukull, W. A., Keene, C. D., Saykin, A. J., Thompson, P. M., Martin, E. R., Bennett, D. A., Barnes, L. L., Schneider, J. A., Crane, P. K., Dumitrescu, L., & Hohman T. J. | 20 | 2 | 1268-1283 | "Introduction: Although large-scale genome-wide association studies (GWAS) have been conducted on AD, few have been conducted on continuous measures of memory performance and memory decline. Methods: We conducted a cross-ancestry GWAS on memory performance (in 27,633 participants) and memory decline (in 22,365 participants; 129,201 observations) by leveraging harmonized cognitive data from four aging cohorts. Results: We found high heritability for two ancestry backgrounds. Further, we found a novel ancestry locus for memory decline on chromosome 4 (rs6848524) and three loci in the non-Hispanic Black ancestry group for memory performance on chromosomes 2 (rs111471504), 7 (rs4142249), and 15 (rs74381744). In our gene-level analysis, we found novel genes for memory decline on chromosomes 1 (SLC25A44), 11 (BSX), and 15 (DPP8). Memory performance and memory decline shared genetic architecture with AD-related traits, neuropsychiatric traits, and autoimmune traits. Discussion: We discovered several novel loci, genes, and genetic correlations associated with late-life memory performance and decline. Highlights: Late-life memory has high heritability that is similar across ancestries. We discovered four novel variants associated with late-life memory. We identified four novel genes associated with late-life memory. Late-life memory shares genetic architecture with psychiatric/autoimmune traits." | PubMed Link | PMC10896586 |
| Measuring Subjective Cognitive Decline in Older Adults: Harmonization Between the Cognitive Change Index and the Measurement of Everyday Cognition Instruments. | Journal of Alzheimer's Disease | 2022 | Wells, L. F., Risacher, S. L., McDonald, B. C., Farlow, M. R., Brosch, J., Gao, S., Apostolova, L. G., Saykin, A. J., & Alzheimer's Disease Neuroimaging Initiative. | 87 | 2 | 761-769 | "Background: Self and informant (proxy or study partner) reports of everyday cognitive functioning have been shown to be associated with incipient neurodegenerative disease. The 20-item Cognitive Change Index (CCI) and the 39-item Measurement of Everyday Cognition (ECog) were each developed to characterize early subjective changes in cognitive function. Objective: We examined the relationship between CCI and ECog self and informant-based evaluations to determine content overlap and provide a co-calibration for converting between these widely used instruments. Methods: 950 participants (57.1% female, mean age = 71.2 years) from ADNI and the Indiana ADRC with self-based evaluations and 279 participants (60.9% female, mean age = 71.8 years) with informant-based evaluations (Indiana ADRC) were included. Analyzed variables for the CCI and ECog included domain mean scores, memory domain total scores, and total scores for all items. Spearman correlations, regression analyses, and frequency distributions were used to assess the relationship between CCI and ECog. Sex, age, years of education, race/ethnicity, APOE _4 carrier status, and baseline diagnosis were also analyzed as potentially relevant covariates. Results: CCI and ECog total scores were highly correlated for the self (r = 0.795, p < 0.001) and informant-based (r = 0.840, p < 0.001) versions, as expected. Frequency distributions of self and informant total scores were generated and plotted separately. Quadratic regressions for self (r2 = 0.626) and informant (r2 = 0.741) scores were used to create a translation table between the CCI and ECog total scores. Conclusion: Self and informant total scores can be harmonized and translated between the CCI and ECog to facilitate cross-study and longitudinal assessment of perceived cognitive change, an important patient-reported outcome." | PubMed Link | PMC9169561 |
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