Browsing by Author "Davis, Justin W."

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    Association of peripheral blood DNA methylation level with Alzheimer’s disease progression
    (BMC, 2021-10-15) Li, Qingqin S.; Vasanthakumar, Aparna; Davis, Justin W.; Idler, Kenneth B.; Nho, Kwangsik; Waring, Jeffrey F.; Saykin, Andrew J.; Radiology and Imaging Sciences, School of Medicine
    Background: Identifying biomarkers associated with Alzheimer's disease (AD) progression may enable patient enrichment and improve clinical trial designs. Epigenome-wide association studies have revealed correlations between DNA methylation at cytosine-phosphate-guanine (CpG) sites and AD pathology and diagnosis. Here, we report relationships between peripheral blood DNA methylation profiles measured using Infinium® MethylationEPIC BeadChip and AD progression in participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. Results: The rate of cognitive decline from initial DNA sampling visit to subsequent visits was estimated by the slopes of the modified Preclinical Alzheimer Cognitive Composite (mPACC; mPACCdigit and mPACCtrailsB) and Clinical Dementia Rating Scale Sum of Boxes (CDR-SB) plots using robust linear regression in cognitively normal (CN) participants and patients with mild cognitive impairment (MCI), respectively. In addition, diagnosis conversion status was assessed using a dichotomized endpoint. Two CpG sites were significantly associated with the slope of mPACC in CN participants (P < 5.79 × 10-8 [Bonferroni correction threshold]); cg00386386 was associated with the slope of mPACCdigit, and cg09422696 annotated to RP11-661A12.5 was associated with the slope of CDR-SB. No significant CpG sites associated with diagnosis conversion status were identified. Genes involved in cognition and learning were enriched. A total of 19, 13, and 5 differentially methylated regions (DMRs) associated with the slopes of mPACCtrailsB, mPACCdigit, and CDR-SB, respectively, were identified by both comb-p and DMRcate algorithms; these included DMRs annotated to HOXA4. Furthermore, 5 and 19 DMRs were associated with conversion status in CN and MCI participants, respectively. The most significant DMR was annotated to the AD-associated gene PM20D1 (chr1: 205,818,956 to 205,820,014 [13 probes], Sidak-corrected P = 7.74 × 10-24), which was associated with both the slope of CDR-SB and the MCI conversion status. Conclusion: Candidate CpG sites and regions in peripheral blood were identified as associated with the rate of cognitive decline in participants in the ADNI cohort. While we did not identify a single CpG site with sufficient clinical utility to be used by itself due to the observed effect size, a biosignature composed of DNA methylation changes may have utility as a prognostic biomarker for AD progression.
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    Harnessing peripheral DNA methylation differences in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) to reveal novel biomarkers of disease
    (Springer, 2020-06-15) Vasanthakumar, Aparna; Davis, Justin W.; Idler, Kenneth; Waring, Jeffrey F.; Asque, Elizabeth; Riley-Gillis, Bridget; Grosskurth, Shaun; Srivastava, Gyan; Kim, Sungeun; Nho, Kwangsik; Nudelman, Kelly N. H.; Faber, Kelley; Sun, Yu; Foroud, Tatiana M.; Estrada, Karol; Apostolova, Liana G.; Li, Qingqin S.; Saykin, Andrew J.; for the Alzheimer’s Disease Neuroimaging Initiative (ADNI); Radiology and Imaging Sciences, School of Medicine
    Background Alzheimer’s disease (AD) is a chronic progressive neurodegenerative disease impacting an estimated 44 million adults worldwide. The causal pathology of AD (accumulation of amyloid-beta and tau), precedes hallmark symptoms of dementia by more than a decade, necessitating development of early diagnostic markers of disease onset, particularly for new drugs that aim to modify disease processes. To evaluate differentially methylated positions (DMPs) as novel blood-based biomarkers of AD, we used a subset of 653 individuals with peripheral blood (PB) samples in the Alzheimer’s disease Neuroimaging Initiative (ADNI) consortium. The selected cohort of AD, mild cognitive impairment (MCI), and age-matched healthy controls (CN) all had imaging, genetics, transcriptomics, cerebrospinal protein markers, and comprehensive clinical records, providing a rich resource of concurrent multi-omics and phenotypic information on a well-phenotyped subset of ADNI participants. Results In this manuscript, we report cross-diagnosis differential peripheral DNA methylation in a cohort of AD, MCI, and age-matched CN individuals with longitudinal DNA methylation measurements. Epigenome-wide association studies (EWAS) were performed using a mixed model with repeated measures over time with a P value cutoff of 1 × 10−5 to test contrasts of pairwise differential peripheral methylation in AD vs CN, AD vs MCI, and MCI vs CN. The most highly significant differentially methylated loci also tracked with Mini Mental State Examination (MMSE) scores. Differentially methylated loci were enriched near brain and neurodegeneration-related genes (e.g., BDNF, BIN1, APOC1) validated using the genotype tissue expression project portal (GTex). Conclusions Our work shows that peripheral differential methylation between age-matched subjects with AD relative to healthy controls will provide opportunities to further investigate and validate differential methylation as a surrogate of disease. Given the inaccessibility of brain tissue, the PB-associated methylation marks may help identify the stage of disease and progression phenotype, information that would be central to bringing forward successful drugs for AD.
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    Integrative analysis of DNA methylation and gene expression identifies genes associated with biological aging in Alzheimer's disease
    (Wiley, 2022-09-20) Kim, Bo-Hyun; Vasanthakumar, Aparna; Li, Qingqin S.; Nudelman, Kelly N.H.; Risacher, Shannon L.; Davis, Justin W.; Idler, Kenneth; Lee, Jong-Min; Seo, Sang Won; Waring, Jeffrey F.; Saykin, Andrew J.; Nho, Kwangsik; Alzheimer’s Disease Neuroimaging Initiative (ADNI); Radiology and Imaging Sciences, School of Medicine
    Introduction: The acceleration of biological aging is a risk factor for Alzheimer's disease (AD). Here, we performed weighted gene co-expression network analysis (WGCNA) to identify modules and dysregulated genes involved in biological aging in AD. Methods: We performed WGCNA to identify modules associated with biological clocks and hub genes of the module with the highest module significance. In addition, we performed differential expression analysis and association analysis with AD biomarkers. Results: WGCNA identified five modules associated with biological clocks, with the module designated as "purple" showing the strongest association. Functional enrichment analysis revealed that the purple module was related to cell migration and death. Ten genes were identified as hub genes in purple modules, of which CX3CR1 was downregulated in AD and low levels of CX3CR1 expression were associated with AD biomarkers. Conclusion: Network analysis identified genes associated with biological clocks, which suggests the genetic architecture underlying biological aging in AD. Highlights: Examine links between Alzheimer's disease (AD) peripheral transcriptome and biological aging changes. Weighted gene co-expression network analysis (WGCNA) found five modules related to biological aging. Among the hub genes of the module, CX3CR1 was downregulated in AD. The CX3CR1 expression level was associated with cognitive performance and brain atrophy.
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    Telomere Shortening in the Alzheimer’s Disease Neuroimaging Initiative Cohort
    (IOS Press, 2019-09-03) Nudelman, Kelly N. H.; Lin, Jue; Lane, Kathleen A.; Nho, Kwangsik; Kim, Sungeun; Faber, Kelley M.; Risacher, Shannon L.; Foroud, Tatiana M.; Gao, Sujuan; Davis, Justin W.; Weiner, Michael W.; Saykin, Andrew J.; Initiative for the Alzheimer’s Disease Neuroimaging; Medical and Molecular Genetics, School of Medicine
    BACKGROUND: Although shorter telomeres have been associated with Alzheimer’s disease (AD), it is unclear whether longitudinal change in telomere length is associated with AD progression. OBJECTIVE: To investigate the association of telomere length change with AD diagnosis and progression. METHODS: In 653 individuals from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort, T/S ratio (telomere vs. single copy gene), a proxy of telomere length, was measured for up to five visits per participant (N=1918 samples post-QC) using quantitative PCR (qPCR). T/S ratio was adjusted for batch effects and DNA storage time. A mixed effects model was used to evaluate association of telomere length with AD diagnostic group and interaction of age and diagnosis. Another mixed effects model was used to compare T/S ratio changes pre- to post-conversion to MCI or AD to telomere change in participants with stable diagnoses. RESULTS: Shorter telomeres were associated with older age (Effect Size (ES)=−0.23) and male sex (ES=−0.26). Neither baseline T/S ratio (ES=−0.036) nor T/S ratio change (ES=0.046) differed significantly between AD diagnostic groups. MCI/AD converters showed greater, but non-significant, telomere shortening compared to non-converters (ES=−0.186). CONCLUSIONS: Although AD compared to controls showed small, non-significant effects for baseline T/S ratio and T/S ratio shortening, we did observe a larger, though still non-significant effect for greater telomere shortening in converters compared to non-converters. Although our results do not support telomere shortening as a robust biomarker of AD progression, further investigation in larger samples and for subgroups of participants may be informative.