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Item Altered bile acid profile in mild cognitive impairment and Alzheimer's disease: Relationship to neuroimaging and CSF biomarkers(Elsevier, 2019-02) Nho, Kwangsik; Kueider-Paisley, Alexandra; MahmoudianDehkordi, Siamak; Arnold, Matthias; Risacher, Shannon L.; Louie, Gregory; Blach, Colette; Baillie, Rebecca; Han, Xianlin; Kastenmüller, Gabi; Jia, Wei; Xie, Guoxiang; Ahmad, Shahzad; Hankemeier, Thomas; van Duijn, Cornelia M.; Trojanowski, John Q.; Shaw, Leslie M.; Weiner, Michael W.; Doraiswamy, P. Murali; Saykin, Andrew J.; Kaddurah-Daouk, Rima; Radiology and Imaging Sciences, School of MedicineINTRODUCTION: Bile acids (BAs) are the end products of cholesterol metabolism produced by human and gut microbiome co-metabolism. Recent evidence suggests gut microbiota influence pathological features of Alzheimer's disease (AD) including neuroinflammation and amyloid-β deposition. METHOD: Serum levels of 20 primary and secondary BA metabolites from the AD Neuroimaging Initiative (n = 1562) were measured using targeted metabolomic profiling. We assessed the association of BAs with the "A/T/N" (amyloid, tau, and neurodegeneration) biomarkers for AD: cerebrospinal fluid (CSF) biomarkers, atrophy (magnetic resonance imaging), and brain glucose metabolism ([18F]FDG PET). RESULTS: Of 23 BAs and relevant calculated ratios after quality control procedures, three BA signatures were associated with CSF Aβ1-42 ("A") and three with CSF p-tau181 ("T") (corrected P < .05). Furthermore, three, twelve, and fourteen BA signatures were associated with CSF t-tau, glucose metabolism, and atrophy ("N"), respectively (corrected P < .05). DISCUSSION: This is the first study to show serum-based BA metabolites are associated with "A/T/N" AD biomarkers, providing further support for a role of BA pathways in AD pathophysiology. Prospective clinical observations and validation in model systems are needed to assess causality and specific mechanisms underlying this association.Item APOE ε2 resilience for Alzheimer's disease is mediated by plasma lipid species: Analysis of three independent cohort studies(Wiley, 2022) Wang, Tingting; Huynh, Kevin; Giles, Corey; Mellett, Natalie A.; Duong, Thy; Nguyen, Anh; Lim, Wei Ling Florence; Smith, Alex At; Olshansky, Gavriel; Cadby, Gemma; Hung, Joseph; Hui, Jennie; Beilby, John; Watts, Gerald F.; Chatterjee, Pratishtha; Martins, Ian; Laws, Simon M.; Bush, Ashley I.; Rowe, Christopher C.; Villemagne, Victor L.; Ames, David; Masters, Colin L.; Taddei, Kevin; Doré, Vincent; Fripp, Jürgen; Arnold, Matthias; Kastenmüller, Gabi; Nho, Kwangsik; Saykin, Andrew J.; Baillie, Rebecca; Han, Xianlin; Martins, Ralph N.; Moses, Eric K.; Kaddurah-Daouk, Rima; Meikle, Peter J.; Radiology and Imaging Sciences, School of MedicineIntroduction: The apolipoprotein E (APOE) genotype is the strongest genetic risk factor for late-onset Alzheimer's disease. However, its effect on lipid metabolic pathways, and their mediating effect on disease risk, is poorly understood. Methods: We performed lipidomic analysis on three independent cohorts (the Australian Imaging, Biomarkers and Lifestyle [AIBL] flagship study, n = 1087; the Alzheimer's Disease Neuroimaging Initiative [ADNI] 1 study, n = 819; and the Busselton Health Study [BHS], n = 4384), and we defined associations between APOE ε2 and ε4 and 569 plasma/serum lipid species. Mediation analysis defined the proportion of the treatment effect of the APOE genotype mediated by plasma/serum lipid species. Results: A total of 237 and 104 lipid species were associated with APOE ε2 and ε4, respectively. Of these 68 (ε2) and 24 (ε4) were associated with prevalent Alzheimer's disease. Individual lipid species or lipidomic models of APOE genotypes mediated up to 30% and 10% of APOE ε2 and ε4 treatment effect, respectively. Discussion: Plasma lipid species mediate the treatment effect of APOE genotypes on Alzheimer's disease and as such represent a potential therapeutic target.Item Association of Altered Liver Enzymes With Alzheimer Disease Diagnosis, Cognition, Neuroimaging Measures, and Cerebrospinal Fluid Biomarkers(American Medical Association, 2019-07) Nho, Kwangsik; Kueider-Paisley, Alexandra; Ahmad, Shahzad; MahmoudianDehkordi, Siamak; Arnold, Matthias; Risacher, Shannon L.; Louie, Gregory; Blach, Colette; Baillie, Rebecca; Han, Xianlin; Kastenmüller, Gabi; Trojanowski, John Q.; Shaw, Leslie M.; Weiner, Michael W.; Doraiswamy, P. Murali; van Duijn, Cornelia; Saykin, Andrew J.; Kaddurah-Daouk, Rima; Radiology and Imaging Sciences, School of MedicineImportance: Increasing evidence suggests an important role of liver function in the pathophysiology of Alzheimer disease (AD). The liver is a major metabolic hub; therefore, investigating the association of liver function with AD, cognition, neuroimaging, and CSF biomarkers would improve the understanding of the role of metabolic dysfunction in AD. Objective: To examine whether liver function markers are associated with cognitive dysfunction and the "A/T/N" (amyloid, tau, and neurodegeneration) biomarkers for AD. Design, Setting, and Participants: In this cohort study, serum-based liver function markers were measured from September 1, 2005, to August 31, 2013, in 1581 AD Neuroimaging Initiative participants along with cognitive measures, cerebrospinal fluid (CSF) biomarkers, brain atrophy, brain glucose metabolism, and amyloid-β accumulation. Associations of liver function markers with AD-associated clinical and A/T/N biomarkers were assessed using generalized linear models adjusted for confounding variables and multiple comparisons. Statistical analysis was performed from November 1, 2017, to February 28, 2019. Exposures: Five serum-based liver function markers (total bilirubin, albumin, alkaline phosphatase, alanine aminotransferase, and aspartate aminotransferase) from AD Neuroimaging Initiative participants were used as exposure variables. Main Outcomes and Measures: Primary outcomes included diagnosis of AD, composite scores for executive functioning and memory, CSF biomarkers, atrophy measured by magnetic resonance imaging, brain glucose metabolism measured by fludeoxyglucose F 18 (18F) positron emission tomography, and amyloid-β accumulation measured by [18F]florbetapir positron emission tomography. Results: Participants in the AD Neuroimaging Initiative (n = 1581; 697 women and 884 men; mean [SD] age, 73.4 [7.2] years) included 407 cognitively normal older adults, 20 with significant memory concern, 298 with early mild cognitive impairment, 544 with late mild cognitive impairment, and 312 with AD. An elevated aspartate aminotransferase (AST) to alanine aminotransferase (ALT) ratio and lower levels of ALT were associated with AD diagnosis (AST to ALT ratio: odds ratio, 7.932 [95% CI, 1.673-37.617]; P = .03; ALT: odds ratio, 0.133 [95% CI, 0.042-0.422]; P = .004) and poor cognitive performance (AST to ALT ratio: β [SE], -0.465 [0.180]; P = .02 for memory composite score; β [SE], -0.679 [0.215]; P = .006 for executive function composite score; ALT: β [SE], 0.397 [0.128]; P = .006 for memory composite score; β [SE], 0.637 [0.152]; P < .001 for executive function composite score). Increased AST to ALT ratio values were associated with lower CSF amyloid-β 1-42 levels (β [SE], -0.170 [0.061]; P = .04) and increased amyloid-β deposition (amyloid biomarkers), higher CSF phosphorylated tau181 (β [SE], 0.175 [0.055]; P = .02) (tau biomarkers) and higher CSF total tau levels (β [SE], 0.160 [0.049]; P = .02) and reduced brain glucose metabolism (β [SE], -0.123 [0.042]; P = .03) (neurodegeneration biomarkers). Lower levels of ALT were associated with increased amyloid-β deposition (amyloid biomarkers), and reduced brain glucose metabolism (β [SE], 0.096 [0.030]; P = .02) and greater atrophy (neurodegeneration biomarkers). Conclusions and Relevance: Consistent associations of serum-based liver function markers with cognitive performance and A/T/N biomarkers for AD highlight the involvement of metabolic disturbances in the pathophysiology of AD. Further studies are needed to determine if these associations represent a causative or secondary role. Liver enzyme involvement in AD opens avenues for novel diagnostics and therapeutics.Item Bile acid synthesis, modulation, and dementia: A metabolomic, transcriptomic, and pharmacoepidemiologic study(PLOS, 2021-05-27) Varma, Vijay R.; Wang, Youjin; An, Yang; Varma, Sudhir; Bilgel, Murat; Doshi, Jimit; Legido-Quigley, Cristina; Delgado, João C.; Oommen, Anup M.; Roberts, Jackson A.; Wong, Dean F.; Davatzikos, Christos; Resnick, Susan M.; Troncoso, Juan C.; Pletnikova, Olga; O’Brien, Richard; Hak, Eelko; Baak, Brenda N.; Pfeiffer, Ruth; Baloni, Priyanka; Mohmoudiandehkordi, Siamak; Nho, Kwangsik; Kaddurah-Daouk, Rima; Bennett, David A.; Gadalla, Shahinaz M.; Thambisetty, Madhav; Radiology and Imaging Sciences, School of MedicineBackground: While Alzheimer disease (AD) and vascular dementia (VaD) may be accelerated by hypercholesterolemia, the mechanisms underlying this association are unclear. We tested whether dysregulation of cholesterol catabolism, through its conversion to primary bile acids (BAs), was associated with dementia pathogenesis. Methods and findings: We used a 3-step study design to examine the role of the primary BAs, cholic acid (CA), and chenodeoxycholic acid (CDCA) as well as their principal biosynthetic precursor, 7α-hydroxycholesterol (7α-OHC), in dementia. In Step 1, we tested whether serum markers of cholesterol catabolism were associated with brain amyloid accumulation, white matter lesions (WMLs), and brain atrophy. In Step 2, we tested whether exposure to bile acid sequestrants (BAS) was associated with risk of dementia. In Step 3, we examined plausible mechanisms underlying these findings by testing whether brain levels of primary BAs and gene expression of their principal receptors are altered in AD. Step 1: We assayed serum concentrations CA, CDCA, and 7α-OHC and used linear regression and mixed effects models to test their associations with brain amyloid accumulation (N = 141), WMLs, and brain atrophy (N = 134) in the Baltimore Longitudinal Study of Aging (BLSA). The BLSA is an ongoing, community-based cohort study that began in 1958. Participants in the BLSA neuroimaging sample were approximately 46% male with a mean age of 76 years; longitudinal analyses included an average of 2.5 follow-up magnetic resonance imaging (MRI) visits. We used the Alzheimer's Disease Neuroimaging Initiative (ADNI) (N = 1,666) to validate longitudinal neuroimaging results in BLSA. ADNI is an ongoing, community-based cohort study that began in 2003. Participants were approximately 55% male with a mean age of 74 years; longitudinal analyses included an average of 5.2 follow-up MRI visits. Lower serum concentrations of 7α-OHC, CA, and CDCA were associated with higher brain amyloid deposition (p = 0.041), faster WML accumulation (p = 0.050), and faster brain atrophy mainly (false discovery rate [FDR] p = <0.001-0.013) in males in BLSA. In ADNI, we found a modest sex-specific effect indicating that lower serum concentrations of CA and CDCA were associated with faster brain atrophy (FDR p = 0.049) in males.Step 2: In the Clinical Practice Research Datalink (CPRD) dataset, covering >4 million registrants from general practice clinics in the United Kingdom, we tested whether patients using BAS (BAS users; 3,208 with ≥2 prescriptions), which reduce circulating BAs and increase cholesterol catabolism, had altered dementia risk compared to those on non-statin lipid-modifying therapies (LMT users; 23,483 with ≥2 prescriptions). Patients in the study (BAS/LMT) were approximately 34%/38% male and with a mean age of 65/68 years; follow-up time was 4.7/5.7 years. We found that BAS use was not significantly associated with risk of all-cause dementia (hazard ratio (HR) = 1.03, 95% confidence interval (CI) = 0.72-1.46, p = 0.88) or its subtypes. We found a significant difference between the risk of VaD in males compared to females (p = 0.040) and a significant dose-response relationship between BAS use and risk of VaD (p-trend = 0.045) in males.Step 3: We assayed brain tissue concentrations of CA and CDCA comparing AD and control (CON) samples in the BLSA autopsy cohort (N = 29). Participants in the BLSA autopsy cohort (AD/CON) were approximately 50%/77% male with a mean age of 87/82 years. We analyzed single-cell RNA sequencing (scRNA-Seq) data to compare brain BA receptor gene expression between AD and CON samples from the Religious Orders Study and Memory and Aging Project (ROSMAP) cohort (N = 46). ROSMAP is an ongoing, community-based cohort study that began in 1994. Participants (AD/CON) were approximately 56%/36% male with a mean age of 85/85 years. In BLSA, we found that CA and CDCA were detectable in postmortem brain tissue samples and were marginally higher in AD samples compared to CON. In ROSMAP, we found sex-specific differences in altered neuronal gene expression of BA receptors in AD. Study limitations include the small sample sizes in the BLSA cohort and likely inaccuracies in the clinical diagnosis of dementia subtypes in primary care settings. Conclusions: We combined targeted metabolomics in serum and amyloid positron emission tomography (PET) and MRI of the brain with pharmacoepidemiologic analysis to implicate dysregulation of cholesterol catabolism in dementia pathogenesis. We observed that lower serum BA concentration mainly in males is associated with neuroimaging markers of dementia, and pharmacological lowering of BA levels may be associated with higher risk of VaD in males. We hypothesize that dysregulation of BA signaling pathways in the brain may represent a plausible biologic mechanism underlying these results. Together, our observations suggest a novel mechanism relating abnormalities in cholesterol catabolism to risk of dementia.Item Bile acids targeted metabolomics and medication classification data in the ADNI1 and ADNIGO/2 cohorts(Nature Research, 2019-10-17) St. John-Williams, Lisa; Mahmoudiandehkordi, Siamak; Arnold, Matthias; Massaro, Tyler; Blach, Colette; Kastenmüller, Gabi; Louie, Gregory; Kueider-Paisley, Alexandra; Han, Xianlin; Baillie, Rebecca; Motsinger-Reif, Alison A.; Rotroff, Daniel; Nho, Kwangsik; Saykin, Andrew J.; Risacher, Shannon L.; Koal, Therese; Moseley, M. Arthur; Tenenbaum, Jessica D.; Thompson, J. Will; Kaddurah-Daouk, Rima; Alzheimer’s Disease Neuroimaging Initiative; Alzheimer’s Disease Metabolomics Consortium; Radiology and Imaging Sciences, School of MedicineAlzheimer’s disease (AD) is the most common cause of dementia. The mechanism of disease development and progression is not well understood, but increasing evidence suggests multifactorial etiology, with a number of genetic, environmental, and aging-related factors. There is a growing body of evidence that metabolic defects may contribute to this complex disease. To interrogate the relationship between system level metabolites and disease susceptibility and progression, the AD Metabolomics Consortium (ADMC) in partnership with AD Neuroimaging Initiative (ADNI) is creating a comprehensive biochemical database for patients in the ADNI1 cohort. We used the Biocrates Bile Acids platform to evaluate the association of metabolic levels with disease risk and progression. We detail the quantitative metabolomics data generated on the baseline samples from ADNI1 and ADNIGO/2 (370 cognitively normal, 887 mild cognitive impairment, and 305 AD). Similar to our previous reports on ADNI1, we present the tools for data quality control and initial analysis. This data descriptor represents the third in a series of comprehensive metabolomics datasets from the ADMC on the ADNI.Item Brain and blood metabolite signatures of pathology and progression in Alzheimer disease: A targeted metabolomics study(Public Library of Science, 2018-01-25) Varma, Vijay R.; Oommen, Anup M.; Varma, Sudhir; Casanova, Ramon; An, Yang; Andrews, Ryan M.; O’Brien, Richard; Pletnikova, Olga; Troncoso, Juan C.; Toledo, Jon; Baillie, Rebecca; Arnold, Matthias; Kastenmueller, Gabi; Nho, Kwangsik; Doraiswamy, P. Murali; Saykin, Andrew J.; Kaddurah-Daouk, Rima; Legido-Quigley, Cristina; Thambisetty, Madhav; Radiology and Imaging Sciences, School of MedicineBACKGROUND: The metabolic basis of Alzheimer disease (AD) is poorly understood, and the relationships between systemic abnormalities in metabolism and AD pathogenesis are unclear. Understanding how global perturbations in metabolism are related to severity of AD neuropathology and the eventual expression of AD symptoms in at-risk individuals is critical to developing effective disease-modifying treatments. In this study, we undertook parallel metabolomics analyses in both the brain and blood to identify systemic correlates of neuropathology and their associations with prodromal and preclinical measures of AD progression. METHODS AND FINDINGS: Quantitative and targeted metabolomics (Biocrates AbsoluteIDQ [identification and quantification] p180) assays were performed on brain tissue samples from the autopsy cohort of the Baltimore Longitudinal Study of Aging (BLSA) (N = 44, mean age = 81.33, % female = 36.36) from AD (N = 15), control (CN; N = 14), and "asymptomatic Alzheimer's disease" (ASYMAD, i.e., individuals with significant AD pathology but no cognitive impairment during life; N = 15) participants. Using machine-learning methods, we identified a panel of 26 metabolites from two main classes-sphingolipids and glycerophospholipids-that discriminated AD and CN samples with accuracy, sensitivity, and specificity of 83.33%, 86.67%, and 80%, respectively. We then assayed these 26 metabolites in serum samples from two well-characterized longitudinal cohorts representing prodromal (Alzheimer's Disease Neuroimaging Initiative [ADNI], N = 767, mean age = 75.19, % female = 42.63) and preclinical (BLSA) (N = 207, mean age = 78.68, % female = 42.63) AD, in which we tested their associations with magnetic resonance imaging (MRI) measures of AD-related brain atrophy, cerebrospinal fluid (CSF) biomarkers of AD pathology, risk of conversion to incident AD, and trajectories of cognitive performance. We developed an integrated blood and brain endophenotype score that summarized the relative importance of each metabolite to severity of AD pathology and disease progression (Endophenotype Association Score in Early Alzheimer's Disease [EASE-AD]). Finally, we mapped the main metabolite classes emerging from our analyses to key biological pathways implicated in AD pathogenesis. We found that distinct sphingolipid species including sphingomyelin (SM) with acyl residue sums C16:0, C18:1, and C16:1 (SM C16:0, SM C18:1, SM C16:1) and hydroxysphingomyelin with acyl residue sum C14:1 (SM (OH) C14:1) were consistently associated with severity of AD pathology at autopsy and AD progression across prodromal and preclinical stages. Higher log-transformed blood concentrations of all four sphingolipids in cognitively normal individuals were significantly associated with increased risk of future conversion to incident AD: SM C16:0 (hazard ratio [HR] = 4.430, 95% confidence interval [CI] = 1.703-11.520, p = 0.002), SM C16:1 (HR = 3.455, 95% CI = 1.516-7.873, p = 0.003), SM (OH) C14:1 (HR = 3.539, 95% CI = 1.373-9.122, p = 0.009), and SM C18:1 (HR = 2.255, 95% CI = 1.047-4.855, p = 0.038). The sphingolipid species identified map to several biologically relevant pathways implicated in AD, including tau phosphorylation, amyloid-β (Aβ) metabolism, calcium homeostasis, acetylcholine biosynthesis, and apoptosis. Our study has limitations: the relatively small number of brain tissue samples may have limited our power to detect significant associations, control for heterogeneity between groups, and replicate our findings in independent, autopsy-derived brain samples. CONCLUSIONS: We present a novel framework to identify biologically relevant brain and blood metabolites associated with disease pathology and progression during the prodromal and preclinical stages of AD. Our results show that perturbations in sphingolipid metabolism are consistently associated with endophenotypes across preclinical and prodromal AD, as well as with AD pathology at autopsy. Sphingolipids may be biologically relevant biomarkers for the early detection of AD, and correcting perturbations in sphingolipid metabolism may be a plausible and novel therapeutic strategy in AD.Item Circular-SWAT for deep learning based diagnostic classification of Alzheimer's disease: application to metabolome data(Elsevier, 2023) Jo, Taeho; Kim, Junpyo; Bice, Paula; Huynh, Kevin; Wang, Tingting; Arnold, Matthias; Meikle, Peter J.; Giles, Corey; Kaddurah-Daouk, Rima; Saykin, Andrew J.; Nho, Kwangsik; Alzheimer’s Disease Metabolomics Consortium (ADMC); Alzheimer’s Disease Neuroimaging Initiative (ADNI); Radiology and Imaging Sciences, School of MedicineBackground: Deep learning has shown potential in various scientific domains but faces challenges when applied to complex, high-dimensional multi-omics data. Alzheimer's Disease (AD) is a neurodegenerative disorder that lacks targeted therapeutic options. This study introduces the Circular-Sliding Window Association Test (c-SWAT) to improve the classification accuracy in predicting AD using serum-based metabolomics data, specifically lipidomics. Methods: The c-SWAT methodology builds upon the existing Sliding Window Association Test (SWAT) and utilizes a three-step approach: feature correlation analysis, feature selection, and classification. Data from 997 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) served as the basis for model training and validation. Feature correlations were analyzed using Weighted Gene Co-expression Network Analysis (WGCNA), and Convolutional Neural Networks (CNN) were employed for feature selection. Random Forest was used for the final classification. Findings: The application of c-SWAT resulted in a classification accuracy of up to 80.8% and an AUC of 0.808 for distinguishing AD from cognitively normal older adults. This marks a 9.4% improvement in accuracy and a 0.169 increase in AUC compared to methods without c-SWAT. These results were statistically significant, with a p-value of 1.04 × 10ˆ-4. The approach also identified key lipids associated with AD, such as Cer(d16:1/22:0) and PI(37:6). Interpretation: Our results indicate that c-SWAT is effective in improving classification accuracy and in identifying potential lipid biomarkers for AD. These identified lipids offer new avenues for understanding AD and warrant further investigation.Item Circulating lipid profiles are associated with cross-sectional and longitudinal changes of central biomarkers for Alzheimer's disease(medRxiv, 2023-06-21) Kim, Jun Pyo; Nho, Kwangsik; Wang, Tingting; Huynh, Kevin; Arnold, Matthias; Risacher, Shannon L.; Bice, Paula J.; Han, Xianlin; Kristal, Bruce S.; Blach, Colette; Baillie, Rebecca; Kastenmüller, Gabi; Meikle, Peter J.; Saykin, Andrew J.; Kaddurah-Daouk, Rima; Alzheimer’s Disease Neuroimaging Initiative; Alzheimer’s Disease Metabolomics Consortium; Radiology and Imaging Sciences, School of MedicineInvestigating the association of lipidome profiles with central Alzheimer's disease (AD) biomarkers, including amyloid/tau/neurodegeneration (A/T/N), can provide a holistic view between the lipidome and AD. We performed cross-sectional and longitudinal association analysis of serum lipidome profiles with AD biomarkers in the Alzheimer's Disease Neuroimaging Initiative cohort (N=1,395). We identified lipid species, classes, and network modules that were significantly associated with cross-sectional and longitudinal changes of A/T/N biomarkers for AD. Notably, we identified the lysoalkylphosphatidylcholine (LPC(O)) as associated with "A/N" biomarkers at baseline at lipid species, class, and module levels. Also, GM3 ganglioside showed significant association with baseline levels and longitudinal changes of the "N" biomarkers at species and class levels. Our study of circulating lipids and central AD biomarkers enabled identification of lipids that play potential roles in the cascade of AD pathogenesis. Our results suggest dysregulation of lipid metabolic pathways as precursors to AD development and progression.Item Comprehensive genetic analysis of the human lipidome identifies loci associated with lipid homeostasis with links to coronary artery disease(Springer Nature, 2022-06-06) Cadby, Gemma; Giles, Corey; Melton, Phillip E.; Huynh, Kevin; Mellett, Natalie A.; Duong, Thy; Nguyen, Anh; Cinel, Michelle; Smith, Alex; Olshansky, Gavriel; Wang, Tingting; Brozynska, Marta; Inouye, Mike; McCarthy, Nina S.; Ariff, Amir; Hung, Joseph; Hui, Jennie; Beilby, John; Dubé, Marie-Pierre; Watts, Gerald F.; Shah, Sonia; Wray, Naomi R.; Lim, Wei Ling Florence; Chatterjee, Pratishtha; Martins, Ian; Laws, Simon M.; Porter, Tenielle; Vacher, Michael; Bush, Ashley I.; Rowe, Christopher C.; Villemagne, Victor L.; Ames, David; Masters, Colin L.; Taddei, Kevin; Arnold, Matthias; Kastenmüller, Gabi; Nho, Kwangsik; Saykin, Andrew J.; Han, Xianlin; Kaddurah-Daouk, Rima; Martins, Ralph N.; Blangero, John; Meikle, Peter J.; Moses, Eric K.; Radiology and Imaging Sciences, School of MedicineWe integrated lipidomics and genomics to unravel the genetic architecture of lipid metabolism and identify genetic variants associated with lipid species putatively in the mechanistic pathway for coronary artery disease (CAD). We quantified 596 lipid species in serum from 4,492 individuals from the Busselton Health Study. The discovery GWAS identified 3,361 independent lipid-loci associations, involving 667 genomic regions (479 previously unreported), with validation in two independent cohorts. A meta-analysis revealed an additional 70 independent genomic regions associated with lipid species. We identified 134 lipid endophenotypes for CAD associated with 186 genomic loci. Associations between independent lipid-loci with coronary atherosclerosis were assessed in ∼456,000 individuals from the UK Biobank. Of the 53 lipid-loci that showed evidence of association (P < 1 × 10-3), 43 loci were associated with at least one lipid endophenotype. These findings illustrate the value of integrative biology to investigate the aetiology of atherosclerosis and CAD, with implications for other complex diseases.Item Concordant peripheral lipidome signatures in two large clinical studies of Alzheimer’s disease(Nature, 2020-11-10) Huynh, Kevin; Lim, Wei Ling Florence; Giles, Corey; Jayawardana, Kaushala S.; Salim, Agus; Mellett, Natalie A.; Smith, Adam Alexander T.; Olshansky, Gavriel; Drew, Brian G.; Chatterjee, Pratishtha; Martins, Ian; Laws, Simon M.; Bush, Ashley I.; Rowe, Christopher C.; Villemagne, Victor L.; Ames, David; Masters, Colin L.; Arnold, Matthias; Nho, Kwangsik; Saykin, Andrew J.; Baillie, Rebecca; Han, Xianlin; Kaddurah-Daouk, Rima; Martins, Ralph N.; Meikle, Peter J.; BioHealth Informatics, School of Informatics and ComputingChanges to lipid metabolism are tightly associated with the onset and pathology of Alzheimer’s disease (AD). Lipids are complex molecules comprising many isomeric and isobaric species, necessitating detailed analysis to enable interpretation of biological significance. Our expanded targeted lipidomics platform (569 species across 32 classes) allows for detailed lipid separation and characterisation. In this study we examined peripheral samples of two cohorts (AIBL, n = 1112 and ADNI, n = 800). We are able to identify concordant peripheral signatures associated with prevalent AD arising from lipid pathways including; ether lipids, sphingolipids (notably GM3 gangliosides) and lipid classes previously associated with cardiometabolic disease (phosphatidylethanolamine and triglycerides). We subsequently identified similar lipid signatures in both cohorts with future disease. Lastly, we developed multivariate lipid models that improved classification and prediction. Our results provide a holistic view between the lipidome and AD using a comprehensive approach, providing targets for further mechanistic investigation., The onset and pathology of Alzheimer’s disease (AD) is associated with changes to lipid metabolism. Here, the authors analysed 569 lipids from 32 classes and subclasses in two independent patient cohorts to identify key lipid pathways to link the plasma lipidome with AD and the future onset of AD.
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