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Chibnik, Lori

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Chibnik

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Lori

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Chibnik, Lori
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    Susceptibility to neurofibrillary tangles: role of the PTPRD locus and limited pleiotropy with other neuropathologies
    (2017) Chibnik, Lori; White, Charles C; Mukherjee, Shubhabrata; Raj, Towfique; Yu, Lei; Larson, Eric B.; Montine, Thomas J.; Keene, C. Dirk; Sonnen, Joshua; Schneider, Julie A.; Crane, Paul K.; Shulman, Joshua M.; Bennett, David A; De Jager, Philip
    Tauopathies, including Alzheimer’s disease (AD) and other neurodegenerative conditions, are defined by a pathological hallmark: neurofibrillary tangles (NFT). NFT accumulation is thought to be closely linked to cognitive decline in AD. Here, we perform a genome-wide association study for NFT pathologic burden and report the association of the PTPRD locus (rs560380, p=3.8×10−8) in 909 prospective autopsies. The association is replicated in an independent dataset of 369 autopsies. The association of PTPRD with NFT is not dependent on the accumulation of amyloid pathology. In contrast, we find that the ZCWPW1 AD susceptibility variant influences NFT accumulation and that this effect is mediated by an accumulation of amyloid β plaques. We also performed complementary analyses to identify common pathways that influence multiple neuropathologies which co-exist with NFT and found suggestive evidence that certain loci may influence multiple different neuropathological traits, including tau, amyloid β plaques, vascular injury and Lewy bodies. Overall, these analyses offer an evaluation of genetic susceptibility to NFT, a common endpoint for multiple different pathologic processes.
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    A randomized controlled trial of an intervention to reduce low literacy barriers in inflammatory arthritis management
    (Elsevier BV, 2009) Rudd, Rima; Blanch, Danielle C.; Gall, Victoria; Chibnik, Lori; Wright, Elizabeth; Reichmann, William; Liang, Matthew; Katz, Jeffrey
    Objective Test the efficacy of educational interventions to reduce literacy barriers and enhance health outcomes among patients with inflammatory arthritis. Methods The intervention consisted of plain language information materials and/or two individualized sessions with an arthritis educator. Randomization was stratified by education level. Principal outcomes included adherence to treatments, self-efficacy, satisfaction with care, and appointment keeping. Secondary outcomes included health status and mental health. Data were collected at baseline, six, and twelve months post. Results Of the 127 patients, half had education beyond high school and three quarters had disease duration greater than five years. There were no differences in the primary outcome measures between the groups. In mixed models controlling for baseline score and demographic factors, the intervention group showed improvement in mental health score at six and twelve months (3.0 and 3.7 points, respectively), while the control group showed diminished scores (−4.5 and −2.6 points, respectively) (p=0.03 and 0.01). Conclusion While the intervention appears to have had no effect on primary outcomes, further studies with continued attention to literacy are warranted. Study site and disease duration must be considered as participants in this study had higher than average health literacy and had established diagnoses for years prior to this study. Practice Implications The study offers insight into an application of many of the protocols currently recommended to ameliorate effects of limited literacy.
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    Modeling Disease Severity in Multiple Sclerosis Using Electronic Health Records
    (Public Library of Science, 2013) Xia, Zongqi; Secor, Elizabeth; Chibnik, Lori; Bove, Riley; Cheng, Suchun; Chitnis, Tanuja; Cagan, Andrew; Gainer, Vivian S.; Chen, Pei J.; Liao, Katherine; Shaw, Stanley; Ananthakrishnan, Ashwin; Szolovits, Peter; Weiner, Howard; Karlson, Elizabeth; Murphy, Shawn; Savova, Guergana; Cai, Tianxi; Churchill, Susanne E.; Plenge, Robert M.; Kohane, Isaac; De Jager, Philip
    Objective: To optimally leverage the scalability and unique features of the electronic health records (EHR) for research that would ultimately improve patient care, we need to accurately identify patients and extract clinically meaningful measures. Using multiple sclerosis (MS) as a proof of principle, we showcased how to leverage routinely collected EHR data to identify patients with a complex neurological disorder and derive an important surrogate measure of disease severity heretofore only available in research settings. Methods: In a cross-sectional observational study, 5,495 MS patients were identified from the EHR systems of two major referral hospitals using an algorithm that includes codified and narrative information extracted using natural language processing. In the subset of patients who receive neurological care at a MS Center where disease measures have been collected, we used routinely collected EHR data to extract two aggregate indicators of MS severity of clinical relevance multiple sclerosis severity score (MSSS) and brain parenchymal fraction (BPF, a measure of whole brain volume). Results: The EHR algorithm that identifies MS patients has an area under the curve of 0.958, 83% sensitivity, 92% positive predictive value, and 89% negative predictive value when a 95% specificity threshold is used. The correlation between EHR-derived and true MSSS has a mean R2 = 0.38±0.05, and that between EHR-derived and true BPF has a mean R2 = 0.22±0.08. To illustrate its clinical relevance, derived MSSS captures the expected difference in disease severity between relapsing-remitting and progressive MS patients after adjusting for sex, age of symptom onset and disease duration (p = 1.56×10−12). Conclusion: Incorporation of sophisticated codified and narrative EHR data accurately identifies MS patients and provides estimation of a well-accepted indicator of MS severity that is widely used in research settings but not part of the routine medical records. Similar approaches could be applied to other complex neurological disorders.
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    The PSEN1, p.E318G Variant Increases the Risk of Alzheimer's Disease in APOE-ε4 Carriers
    (Public Library of Science, 2013) Benitez, Bruno A.; Karch, Celeste M.; Cai, Yefei; Jin, Sheng Chih; Cooper, Breanna; Carrell, David; Bertelsen, Sarah; Chibnik, Lori; Schneider, Julie A.; Bennett, David A.; Fagan, Anne M.; Holtzman, David; Morris, John C.; Goate, Alison M.; Cruchaga, Carlos
    The primary constituents of plaques (Aβ42/Aβ40) and neurofibrillary tangles (tau and phosphorylated forms of tau [ptau]) are the current leading diagnostic and prognostic cerebrospinal fluid (CSF) biomarkers for AD. In this study, we performed deep sequencing of APP, PSEN1, PSEN2, GRN, APOE and MAPT genes in individuals with extreme CSF Aβ42, tau, or ptau levels. One known pathogenic mutation (PSEN1 p.A426P), four high-risk variants for AD (APOE p.L46P, MAPT p.A152T, PSEN2 p.R62H and p.R71W) and nine novel variants were identified. Surprisingly, a coding variant in PSEN1, p.E318G (rs17125721-G) exhibited a significant association with high CSF tau (p = 9.2×10−4) and ptau (p = 1.8×10−3) levels. The association of the p.E318G variant with Aβ deposition was observed in APOE-ε4 allele carriers. Furthermore, we found that in a large case-control series (n = 5,161) individuals who are APOE-ε4 carriers and carry the p.E318G variant are at a risk of developing AD (OR = 10.7, 95% CI = 4.7–24.6) that is similar to APOE-ε4 homozygous (OR = 9.9, 95% CI = 7.2.9–13.6), and double the risk for APOE-ε4 carriers that do not carry p.E318G (OR = 3.9, 95% CI = 3.4–4.4). The p.E318G variant is present in 5.3% (n = 30) of the families from a large clinical series of LOAD families (n = 565) and exhibited a higher frequency in familial LOAD (MAF = 2.5%) than in sporadic LOAD (MAF = 1.6%) (p = 0.02). Additionally, we found that in the presence of at least one APOE-ε4 allele, p.E318G is associated with more Aβ plaques and faster cognitive decline. We demonstrate that the effect of PSEN1, p.E318G on AD susceptibility is largely dependent on an interaction with APOE-ε4 and mediated by an increased burden of Aβ deposition.
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    CD33 Alzheimer’s disease locus: Altered monocyte function and amyloid biology
    (2013) Bradshaw, Elizabeth M.; Chibnik, Lori; Keenan, Brendan T; Ottoboni, Linda; Raj, Towfique; Tang, Anna; Rosenkrantz, Laura L; Imboywa, Selina; Lee, Michelle Ann; Von Korff, Alina; Morris, Martha C; Evans, Denis A; Johnson, Keith; Sperling, Reisa; Schneider, Julie A; Bennett, David A; De Jager, Philip
    In our functional dissection of the CD33 Alzheimer’s disease susceptibility locus, we find that the rs3865444C risk allele is associated with greater cell surface expression of CD33 in monocytes (t50 = 10.06, pjoint=1.3×10–13) of young and older individuals. It is also associated with (1) diminished internalization of Aβ42) (2) accumulation of neuritic amyloid pathology and fibrillar amyloid on in vivo imaging and (3), increased numbers of activated human microglia.
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    24-Hour Rhythms of DNA Methylation and Their Relation with Rhythms of RNA Expression in the Human Dorsolateral Prefrontal Cortex
    (Public Library of Science, 2014) Lim, Andrew S. P.; Srivastava, Gyan; Yu, Lei; Chibnik, Lori; Xu, Jishu; Buchman, Aron S.; Schneider, Julie A.; Myers, Amanda J.; Bennett, David A.; De Jager, Philip
    Circadian rhythms modulate the biology of many human tissues, including brain tissues, and are driven by a near 24-hour transcriptional feedback loop. These rhythms are paralleled by 24-hour rhythms of large portions of the transcriptome. The role of dynamic DNA methylation in influencing these rhythms is uncertain. While recent work in Neurospora suggests that dynamic site-specific circadian rhythms of DNA methylation may play a role in modulating the fungal molecular clock, such rhythms and their relationship to RNA expression have not, to our knowledge, been elucidated in mammalian tissues, including human brain tissues. We hypothesized that 24-hour rhythms of DNA methylation exist in the human brain, and play a role in driving 24-hour rhythms of RNA expression. We analyzed DNA methylation levels in post-mortem human dorsolateral prefrontal cortex samples from 738 subjects. We assessed for 24-hour rhythmicity of 420,132 DNA methylation sites throughout the genome by considering methylation levels as a function of clock time of death and parameterizing these data using cosine functions. We determined global statistical significance by permutation. We then related rhythms of DNA methylation with rhythms of RNA expression determined by RNA sequencing. We found evidence of significant 24-hour rhythmicity of DNA methylation. Regions near transcription start sites were enriched for high-amplitude rhythmic DNA methylation sites, which were in turn time locked to 24-hour rhythms of RNA expression of nearby genes, with the nadir of methylation preceding peak transcript expression by 1–3 hours. Weak ante-mortem rest-activity rhythms were associated with lower amplitude DNA methylation rhythms as were older age and the presence of Alzheimer's disease. These findings support the hypothesis that 24-hour rhythms of DNA methylation, particularly near transcription start sites, may play a role in driving 24-hour rhythms of gene expression in the human dorsolateral prefrontal cortex, and may be affected by age and Alzheimer's disease.
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    Alzheimer’s loci: epigenetic associations and interaction with genetic factors
    (John Wiley & Sons, Ltd, 2015) Chibnik, Lori; Yu, Lei; Eaton, Matthew L; Srivastava, Gyan; Schneider, Julie A; Kellis, Manolis; Bennett, David A; De Jager, Philip
    Objective: We explore the role of DNA methylation in Alzheimer’s disease (AD). To elucidate where DNA methylation falls along the causal pathway linking risk factors to disease, we examine causal models to assess its role in the pathology of AD. Methods: DNA methylation profiles were generated in 740 brain samples using the Illumina HumanMet450K beadset. We focused our analysis on CpG sites from 11 AD susceptibility gene regions. The primary outcome was a quantitative measure of neuritic amyloid plaque (NP), a key early element of AD pathology. We tested four causal models: (1) independent associations, (2) CpG mediating the association of a variant, (3) reverse causality, and (4) genetic variant by CpG interaction. Results: Six genes regions (17 CpGs) showed evidence of CpG associations with NP, independent of genetic variation – BIN1 (5), CLU (5), MS4A6A (3), ABCA7 (2), CD2AP (1), and APOE (1). Together they explained 16.8% of the variability in NP. An interaction effect was seen in the CR1 region for two CpGs, cg10021878 (P = 0.01) and cg05922028 (P = 0.001), in relation to NP. In both cases, subjects with the risk allele rs6656401AT/AA display more methylation being associated with more NP burden, whereas subjects with the rs6656401TT protective genotype have an inverse association with more methylation being associated with less NP. Interpretation These observations suggest that, within known AD susceptibility loci, methylation is related to pathologic processes of AD and may play a largely independent role by influencing gene expression in AD susceptibility loci.
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    Complex relation of HLA-DRB1*1501, age at menarche, and age at multiple sclerosis onset
    (Wolters Kluwer, 2016) Bove, Riley; Chua, Alicia S.; Xia, Zongqi; Chibnik, Lori; De Jager, Philip; Chitnis, Tanuja
    Objective: To examine the relationship between 2 markers of early multiple sclerosis (MS) onset, 1 genetic (HLA-DRB1*1501) and 1 experiential (early menarche), in 2 cohorts. Methods: We included 540 white women with MS or clinically isolated syndrome (N = 156 with genetic data available) and 1,390 white women without MS but with a first-degree relative with MS (Genes and Environment in Multiple Sclerosis [GEMS]). Age at menarche, HLA-DRB1*1501 status, and age at MS onset were analyzed. Results: In both cohorts, participants with at least 1 HLA-DRB1*1501 allele had a later age at menarche than did participants with no risk alleles (MS: mean difference = 0.49, 95% confidence interval [CI] = [0.03–0.95], p = 0.036; GEMS: mean difference = 0.159, 95% CI = [0.012–0.305], p = 0.034). This association remained after we adjusted for body mass index at age 18 (available in GEMS) and for other MS risk alleles, as well as a single nucleotide polymorphism near the HLA-A region previously associated with age of menarche (available in MS cohort). Confirming previously reported associations, in our MS cohort, every year decrease in age at menarche was associated with a 0.65-year earlier MS onset (95% CI = [0.07–1.22], p = 0.027, N = 540). Earlier MS onset was also found in individuals with at least 1 HLA-DRB1*1501 risk allele (mean difference = −3.40 years, 95% CI = [−6.42 to −0.37], p = 0.028, N = 156). Conclusions: In 2 cohorts, a genetic marker for earlier MS onset (HLA-DRB1*1501) was inversely related to earlier menarche, an experiential marker for earlier symptom onset. This finding warrants broader investigations into the association between the HLA region and hormonal regulation in determining the onset of autoimmune disease.
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    Trans-pQTL study identifies immune crosstalk between Parkinson and Alzheimer loci
    (Wolters Kluwer, 2016) Chan, Gail; White, Charles C.; Winn, Phoebe A.; Cimpean, Maria; Replogle, Joseph M.; Glick, Laura R.; Cuerdon, Nicole E.; Ryan, Katie J.; Johnson, Keith; Schneider, Julie A.; Bennett, David A.; Chibnik, Lori; Sperling, Reisa; De Jager, Philip; Bradshaw, Elizabeth M.
    Objective: Given evidence from genetic studies, we hypothesized that there may be a shared component to the role of myeloid function in Parkinson and Alzheimer disease (PD and AD) and assessed whether PD susceptibility variants influenced protein expression of well-established AD-associated myeloid genes in human monocytes. Methods: We repurposed data in which AD-related myeloid proteins CD33, TREM1, TREM2, TREML2, TYROBP, and PTK2B were measured by flow cytometry in monocytes from 176 participants of the PhenoGenetic Project (PGP) and Harvard Aging Brain Study. Linear regression was used to identify associations between 24 PD risk variants and protein expression. The 2 cohorts were meta-analyzed in a discovery analysis, and the 4 most strongly suggestive results were validated in an independent cohort of 50 PGP participants. Results: We discovered and validated an association between the PD risk allele rs12456492G in the RIT2 locus and increased CD33 expression (pjoint = 3.50 × 10−5) and found strongly suggestive evidence that rs11060180A in the CCDC62/HIP1R locus decreased PTK2B expression (pjoint = 1.12 × 10−4). Furthermore, in older individuals, increased CD33 expression on peripheral monocytes was associated with a greater burden of parkinsonism (p = 0.047), particularly bradykinesia (p = 6.64 × 10−3). Conclusions: We find that the rs12456492 PD risk variant affects expression of AD-associated protein CD33 in peripheral monocytes, which suggests that genetic factors for these 2 diseases may converge to influence overlapping innate immune-mediated mechanisms that contribute to neurodegeneration. Furthermore, the effect of the rs12456492G PD risk allele on increased CD33 suggests that the inhibition of certain myeloid functions may contribute to PD susceptibility, as is the case for AD.
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    Diurnal and seasonal molecular rhythms in human neocortex and their relation to Alzheimer's disease
    (Nature Publishing Group, 2017) Lim, Andrew S. P.; Klein, Hans-Ulrich; Yu, Lei; Chibnik, Lori; Ali, Sanam; Xu, Jishu; Bennett, David A.; De Jager, Philip
    Circadian and seasonal rhythms are seen in many species, modulate several aspects of human physiology, including brain functions such as mood and cognition, and influence many neurological and psychiatric illnesses. However, there are few data regarding the genome-scale molecular correlates underlying these rhythms, especially in the human brain. Here, we report widespread, site-specific and interrelated diurnal and seasonal rhythms of gene expression in the human brain, and show their relationship with parallel rhythms of epigenetic modification including histone acetylation, and DNA methylation. We also identify transcription factor-binding sites that may drive these effects. Further, we demonstrate that Alzheimer's disease pathology disrupts these rhythms. These data suggest that interrelated diurnal and seasonal epigenetic and transcriptional rhythms may be an important feature of human brain biology, and perhaps human biology more broadly, and that changes in such rhythms may be consequences of, or contributors to, diseases such as Alzheimer's disease.