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191 results on '"Zhou, Xiaopu"'

1. Deep learning-based polygenic risk analysis for Alzheimer’s disease prediction

Author

Zhou, Xiaopu, Chen, Yu, Ip, Fanny CF, Jiang, Yuanbing, Cao, Han, Lv, Ge, Zhong, Huan, Chen, Jiahang, Ye, Tao, Chen, Yuewen, Zhang, Yulin, Ma, Shuangshuang, Lo, Ronnie MN, Tong, Estella PS, Mok, Vincent CT, Kwok, Timothy CY, Guo, Qihao, Mok, Kin Y, Shoai, Maryam, Hardy, John, Chen, Lei, Fu, Amy KY, and Ip, Nancy Y

Subjects
Information and Computing Sciences, Biological Sciences, Genetics, Machine Learning, Neurosciences, Brain Disorders, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Dementia, Machine Learning and Artificial Intelligence, Neurodegenerative, Networking and Information Technology R&D (NITRD), Bioengineering, Acquired Cognitive Impairment, Alzheimer's Disease, Prevention, Aging, Human Genome, 2.1 Biological and endogenous factors, 4.1 Discovery and preclinical testing of markers and technologies, 2.5 Research design and methodologies (aetiology), Neurological, Good Health and Well Being, Alzheimer’s Disease Neuroimaging Initiative
Abstract

BackgroundThe polygenic nature of Alzheimer's disease (AD) suggests that multiple variants jointly contribute to disease susceptibility. As an individual's genetic variants are constant throughout life, evaluating the combined effects of multiple disease-associated genetic risks enables reliable AD risk prediction. Because of the complexity of genomic data, current statistical analyses cannot comprehensively capture the polygenic risk of AD, resulting in unsatisfactory disease risk prediction. However, deep learning methods, which capture nonlinearity within high-dimensional genomic data, may enable more accurate disease risk prediction and improve our understanding of AD etiology. Accordingly, we developed deep learning neural network models for modeling AD polygenic risk.MethodsWe constructed neural network models to model AD polygenic risk and compared them with the widely used weighted polygenic risk score and lasso models. We conducted robust linear regression analysis to investigate the relationship between the AD polygenic risk derived from deep learning methods and AD endophenotypes (i.e., plasma biomarkers and individual cognitive performance). We stratified individuals by applying unsupervised clustering to the outputs from the hidden layers of the neural network model.ResultsThe deep learning models outperform other statistical models for modeling AD risk. Moreover, the polygenic risk derived from the deep learning models enables the identification of disease-associated biological pathways and the stratification of individuals according to distinct pathological mechanisms.ConclusionOur results suggest that deep learning methods are effective for modeling the genetic risks of AD and other diseases, classifying disease risks, and uncovering disease mechanisms.

Published
2023

2. SNP2Vec: Scalable Self-Supervised Pre-Training for Genome-Wide Association Study

Author

Cahyawijaya, Samuel, Yu, Tiezheng, Liu, Zihan, Mak, Tiffany T. W., Zhou, Xiaopu, Ip, Nancy Y., and Fung, Pascale

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract

Self-supervised pre-training methods have brought remarkable breakthroughs in the understanding of text, image, and speech. Recent developments in genomics has also adopted these pre-training methods for genome understanding. However, they focus only on understanding haploid sequences, which hinders their applicability towards understanding genetic variations, also known as single nucleotide polymorphisms (SNPs), which is crucial for genome-wide association study. In this paper, we introduce SNP2Vec, a scalable self-supervised pre-training approach for understanding SNP. We apply SNP2Vec to perform long-sequence genomics modeling, and we evaluate the effectiveness of our approach on predicting Alzheimer's disease risk in a Chinese cohort. Our approach significantly outperforms existing polygenic risk score methods and all other baselines, including the model that is trained entirely with haploid sequences. We release our code and dataset on https://github.com/HLTCHKUST/snp2vec.

Published
2022

3. An IL1RL1 genetic variant lowers soluble ST2 levels and the risk effects of APOE-ε4 in female patients with Alzheimer's disease.

Author

Jiang, Yuanbing, Zhou, Xiaopu, Wong, Hiu Yi, Ouyang, Li, Ip, Fanny CF, Chau, Vicky MN, Lau, Shun-Fat, Wu, Wei, Wong, Daniel YK, Seo, Heukjin, Fu, Wing-Yu, Lai, Nicole CH, Chen, Yuewen, Chen, Yu, Tong, Estella PS, Alzheimer’s Disease Neuroimaging Initiative, Mok, Vincent CT, Kwok, Timothy CY, Mok, Kin Y, Shoai, Maryam, Lehallier, Benoit, Losada, Patricia Morán, O'Brien, Eleanor, Porter, Tenielle, Laws, Simon M, Hardy, John, Wyss-Coray, Tony, Masters, Colin L, Fu, Amy KY, and Ip, Nancy Y

Subjects
Alzheimer’s Disease Neuroimaging Initiative, Animals, Humans, Mice, Alzheimer Disease, Female, Apolipoprotein E4, Genome-Wide Association Study, Amyloid beta-Peptides, Interleukin-1 Receptor-Like 1 Protein, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Human Genome, Brain Disorders, Dementia, Neurosciences, Alzheimer's Disease, Aging, Neurodegenerative, Genetics, Acquired Cognitive Impairment, Aetiology, 2.1 Biological and endogenous factors, Neurological
Abstract

Changes in the levels of circulating proteins are associated with Alzheimer's disease (AD), whereas their pathogenic roles in AD are unclear. Here, we identified soluble ST2 (sST2), a decoy receptor of interleukin-33-ST2 signaling, as a new disease-causing factor in AD. Increased circulating sST2 level is associated with more severe pathological changes in female individuals with AD. Genome-wide association analysis and CRISPR-Cas9 genome editing identified rs1921622 , a genetic variant in an enhancer element of IL1RL1, which downregulates gene and protein levels of sST2. Mendelian randomization analysis using genetic variants, including rs1921622 , demonstrated that decreased sST2 levels lower AD risk and related endophenotypes in females carrying the Apolipoprotein E (APOE)-ε4 genotype; the association is stronger in Chinese than in European-descent populations. Human and mouse transcriptome and immunohistochemical studies showed that rs1921622 /sST2 regulates amyloid-beta (Aβ) pathology through the modulation of microglial activation and Aβ clearance. These findings demonstrate how sST2 level is modulated by a genetic variation and plays a disease-causing role in females with AD.

Published
2022

4. Identification of genetic risk loci and causal insights associated with Parkinson's disease in African and African admixed populations: a genome-wide association study

Author

Okubadejo, Njideka, Ojo, Oluwadamilola, Abiodun, Oladunni, Achoru, Charles, Agabi, Osigwe, Agulanna, Uchechi, Akinyemi, Rufus, Ali, Mohammed, Ani-Osheku, Ifeyinwa, Arigbodi, Ohwotemu, Bello, Abiodun, Erameh, Cyril, Farombi, Temitope, Fawale, Michael, Imarhiagbe, Frank, Iwuozo, Emmanuel, Komolafe, Morenikeji, Nwani, Paul, Nwazor, Ernest, Nyandaiti, Yakub, Obiabo, Yahaya, Odeniyi, Olanike, Odiase, Francis, Ojini, Francis, Onwuegbuzie, Gerald, Osaigbovo, Godwin, Osemwegie, Nosakhare, Oshinaike, Olajumoke, Otubogun, Folajimi, Oyakhire, Shyngle, Ozomma, Simon, Samuel, Sarah, Taiwo, Funmilola, Wahab, Kolawole, Zubair, Yusuf, Gams Massi, Daniel, Gueumekane Bila lamou, Eric, Njamnshi Nfor, Leonard, Magnerou, Mélanie Annick, Fogang Fogoum, Yannick, Shalash, Ali, El-FawaI, Hassan, Khedr, Eman, Fawi, Gharib, A. Eltantawi, Mohamed, Salama, Mohamed, El-Jaafary, Shaimaa, Hamed, Sharifa, Tafesse Mengesha, Abenet, Alemayehu Ayele, Biniyam, Melka Oda, Dereje, Zenebe Zewde, Yared, Debebe Gelan, Yohanesse, AkpaIu, Albert, Charway-Felli, Augustina, Stephen Sarfo, Fred, Adjei, Patrick, Obese, Vida, Bocoum, Abdoulaye, Koita, Abdou, Oumar Guinto, Cheick, Coulibaly, Toumany, Maiga, Youssoufa, Kone, Zaynab, Bell, Abiodun, Adebowale, Akintunde A., Akpekpe, John, lyagba, Alagoma, Wulgo, Ali Mohammed, Arabambi, Babawale, Agu, Christian, Dike, Franklin, Ishola, Ismail, Abiodun, Kehinde, Ekenze, Oluchi, Agabi Osigwe, Paul, Balarabe, Salisu, Abubakar, Sani, Williams, Uduak, Fall, Maouly, Mamadou Diop, Alassane, Hilaire Dominique, Ewodo Touna, Mochan, Andre, Modi, Girish, Dindayal, Saiesha, Ali Awadelkareem, Eman, Elsayed, Inas, Dahawi, Maha, Awadelkareem, Mosab Ali, Misbah, Sarah, Mushengez, Brighton, Kimambo, Henrika, Msango, Leonard, Adebayo, Philip, OKeng, Kigocha, Diekker, Marieke, URassa, Sarah, Gouider, Riadh, Ben Djebara, Mouna, Gargouri, Amina, Kacem, Imen, Nasri, Amina, Mrabet, Saloua, Sghaier, Ikram, Mkada, Imen, Atadzhanov, Masharip, Chishimba, Lorraine, Rizig, Mie, Jama, Fatumah, Okunoye, Olaitan, Hardy, John, Houlden, Henry, Singleton, Andrew, Nalls, Mike, Shamim, Ejaz, Jonas, Cabell, Williamson, Jared, Hall, Deborah A., Rosenbaum, Marc, Davis, Staci, Dean, Marissa, Cromer, Candace, Smith, Jenna, Ruffrage, Lauren, Richardson, Joseph, Sipma, Rebeka, Xie, Tao, Padmanaban, Manesh, Warren, Natalie, Mercado, Tomas, Disbrow, Elizabeth, Chauppeta, Brian, Thomas-Dean, Fermine, Toms, Jamie, Lofton, Katelyn, Rawls, Ashley, Rizer, Kyle, Black, Nieci, Solle, Justin, O'Grady, Alyssa, Sherer, Todd, Fiske, Brian, Başak, A. Nazlı, Tan, Ai Huey, Noyce, Alastair, Akpalu, Albert, Espay, Alberto, Martínez-Carrasco, Alejandro, Medina, Alex, Zimprich, Alexander, Brice, Alexis, Karimova, Altynay, Hernandez, Alvaro, Illarionova, Anastasia, Quattrone, Andrea, Singleton, Andrew B, Sobering, Andrew K., Vinuela, Angel, Sanyaolu, Arinola, Schumacher-Schuh, Artur F., Kishore, Asha, Ahmad-Annuar, Azlina, Al Mubarak, Bashayer, Tang, Beisha, Pizarro Galleguillos, Benjamin, Jeon, Beomseok, Siddiqi, Bernadette, Casey, Bradford, Mollenhauer, Brit, Carroll, Camille, Rieder, Carlos, Pantazis, Caroline B., Comart, Charisse, Lin, Chin-Hsien, Klein, Christine, Bale, Claire, Shepherd, Claire E, Wegel, Claire, Blauwendraat, Cornelis, Vitale, Dan, Martinez-Ramirez, Daniel, Hall, Deborah, Hernandez, Dena, KP, Divya, Nguyen, Duan, Fon, Edward A., Dadiotis, Efthymios, Riley, Ekemini, Iakovenko, Elena, Stafford, Ellie, Gatto, Emilia M, Valente, Enza Maria, Vollstedt, Eva-Juliane, Faghri, Faraz, Genc, Gencer, Xiromerisiou, Georgia, Hadjigorgiou, Georgios, Hiu-Fai Chan, Germaine, Arboleda, Gonzalo, Kaishibayeva, Gulnaz, Höglinger, Günter, Leonard, Hampton, Madoev, Harutyun, Iwaki, Hirotaka, Chen, Honglei, Wu, Hsiu-Chuan, Shang, Huifang, Morris, Huw R, F. Mata, Ignacio, Keller Sarmiento, Ignacio Juan, Dagklis, Ioannis, Tarnanas, Ioannis, Aasly, Jan O., Hoenicka, Janet, Corvol, Jean-Christophe, Foo, Jia Nee, Guo, Jifeng, Junker, Johanna, Carr, Jonathan, Kim, Jonggeol Jeff, Orozco, Jorge, Jankovic, Joseph, Shulman, Joshua, Hunter, Julie, Solle, Justin C., Murphy, Kaileigh, Nuytemans, Karen, Kieburtz, Karl, Lohmann, Katja, Marek, Kenneth, Mok, Kin Ying, Kumar, Kishore, Levine, Kristin, Chahine, Lana M., Lange, Lara M., Pihlstrøm, Lasse, Screven, Laurel, Stefanis, Leonidas, Shulman, Lisa, Marsili, Luca, Parnetti, Lucilla, Kuhl, Maggie, Funayama, Manabu, Sharma, Manu, Tan, Manuela, Kauffman, Marcelo, Miranda, Marcelo, Bustamante, Maria Leonor, Stamelou, Maria, Periñan Tocino, Maria Teresa, Cornejo-Olivas, Mario, Jimenez del Rio, Marlene, Makarious, Mary B, Koretsky, Mathew, Rodriguez-Violante, Mayela, Ellis, Melina, Avenali, Micol, Rentería, Miguel E., Inca-Martines, Miguel z, Nalls, Mike A., Ibrahim Norlinah, Mohamed, Umair, Muhammad, Ip, Nancy, Louie, Naomi, Cheung, Nelson Yuk-Fai, Mencacci, Niccolò Emanuele, Wood, Nicholas, Williams, Nigel, Hattori, Nobutaka, Abdul Murad, Nor Azian, Ibrahim, Norlinah Mohamed, Monchi, Oury, Öztop Çakmak, Özgür, Öztop Çakmak, Patricio Öztop Çakmak, Lewis, Patrick Alfryn, Pastor, Pau, Reyes-Pérez, Paula, Saffie Awad, Paula, Chana, Pedro, Chan, Phillip, Kung, Pin-Jui, Chan, Piu, Pal, Pramod, Lingappa Kukkle, Prashanth, Ojha, Rajeev, Kaiyrzhanov, Rauan, Krüger, Rejko, Amouri, Rim, Weil, Rimona, Rajan, Roopa, Alcalay, Roy, Wu, Ruey-Meei, Borgohain, Rupam, Sassi, Samia Ben, Khachatryan, Samson, Bandres-Ciga, Sara, El-Sadig, Sarah, Wu, Serena, Groppa, Sergio, Azmin, Shahrul, Lim, Shen-Yang, Ur-Rehman, Shoaib, Ertan, Sibel, Stott, Simon, Jasaitye, Simona, Chowdhury, Sohini, Dumanis, Sonya, Bardien, Soraya, Lubbe, Steven, Koks, Sulev, Dey, Sumit, Foroud, Tatiana, Fon, Ted, Beach, Thomas, Gasser, Thomas, Anderson, Tim, Nguyen, Toan, Schirinzi, Tommaso, Shiraishi, Tomotaka, Pitcher, Toni, Tumas, Vitor, Mohamed, Wael, Kamel, Walaa A., Luo, Wei, Zhou, Xiaopu, Zewde, Yared Z., Song, Yeajin, Wen, Yi, Wu, Yihru, Joong Kim, Yun, Tavadyan, Zaruhi, Fang, Zih-Hua, Ojo, Oluwadamilola Omolara, Crea, Peter Wild, Abiodun, Oladunni Victoria, Levine, Kristin S, Abubakar, Sani Atta, Achoru, Charles Obiora, Adeniji, Olaleye Akinmola, Agabi, Osigwe Paul, Koretsky, Mathew J, Hall, Deborah A, Akinyemi, Rufus Olusola, Ali, Mohammed Wulgo, Shamim, Ejaz A, Padmanaban, Mahesh, Arigbodi, Ohwotemu Michael, Standaert, David G, Bello, Abiodun Hamzat, Dean, Marissa N, Erameh, Cyril Oshomah, Farombi, Temitope Hannah, Fawale, Michael Bimbola, Billingsley, Kimberley J, Imarhiagbe, Frank Aiwansoba, Jerez, Pilar Alvarez, Iwuozo, Emmanuel Uzodinma, Baker, Breeana, Komolafe, Morenikeji Adeyoyin, Malik, Laksh, Nwani, Paul Osemeke, Daida, Kensuke, Nwazor, Ernest Okwundu, Miano-Burkhardt, Abigail, Nyandaiti, Yakub Wilberforce, Obiabo, Yahaya Olugbo, Kluss, Jillian H, Odeniyi, Olanike Adedoyin, Hernandez, Dena G, Odiase, Francis Ehidiamen, Tayebi, Nahid, Ojini, Francis Ibe, Sidranksy, Ellen, Onwuegbuzie, Gerald Awele, D'Souza, Andrea M, Osaigbovo, Godwin Osawaru, Berhe, Bahafta, Reed, Xylena, Oshinaike, Olajumoke Olufemi, Leonard, Hampton L, Otubogun, Folajimi Morenikeji, Alvarado, Chelsea X, Oyakhire, Shyngle Imiewan, Ozomma, Simon Izuchukwu, Samuel, Sarah Chabiri, Taiwo, Funmilola Tolulope, Wahab, Kolawole Wasiu, Zubair, Yusuf Agboola, Kim, Jonggeol Jeffrey, Nalls, Mike A, Heilbron, Karl, Norcliffe-Kaufmann, Lucy, and Okubadejo, Njideka Ulunma

Published
2023
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5. Non-coding variability at the APOE locus contributes to the Alzheimer's risk.

Author

Zhou, Xiaopu, Chen, Yu, Mok, Kin Y, Kwok, Timothy CY, Mok, Vincent CT, Guo, Qihao, Ip, Fanny C, Chen, Yuewen, Mullapudi, Nandita, Alzheimer’s Disease Neuroimaging Initiative, Giusti-Rodríguez, Paola, Sullivan, Patrick F, Hardy, John, Fu, Amy KY, Li, Yun, and Ip, Nancy Y

Subjects
Alzheimer’s Disease Neuroimaging Initiative, Brain, Humans, Alzheimer Disease, Genetic Predisposition to Disease, Apolipoproteins C, Apolipoproteins E, Case-Control Studies, Cognition, Gene Expression, Haplotypes, Polymorphism, Single Nucleotide, Aged, Aged, 80 and over, Middle Aged, Female, Male, Genetic Variation, Nectins, Polymorphism, Single Nucleotide, and over
Abstract

Alzheimer's disease (AD) is a leading cause of mortality in the elderly. While the coding change of APOE-ε4 is a key risk factor for late-onset AD and has been believed to be the only risk factor in the APOE locus, it does not fully explain the risk effect conferred by the locus. Here, we report the identification of AD causal variants in PVRL2 and APOC1 regions in proximity to APOE and define common risk haplotypes independent of APOE-ε4 coding change. These risk haplotypes are associated with changes of AD-related endophenotypes including cognitive performance, and altered expression of APOE and its nearby genes in the human brain and blood. High-throughput genome-wide chromosome conformation capture analysis further supports the roles of these risk haplotypes in modulating chromatin states and gene expression in the brain. Our findings provide compelling evidence for additional risk factors in the APOE locus that contribute to AD pathogenesis.

Published
2019

7. Identification of genetic risk factors in the Chinese population implicates a role of immune system in Alzheimer’s disease pathogenesis

Author

Zhou, Xiaopu, Chen, Yu, Mok, Kin Y, Zhao, Qianhua, Chen, Keliang, Chen, Yuewen, Hardy, John, Li, Yun, Fu, Amy KY, Guo, Qihao, Ip, Nancy Y, Saykin, Andrew J, Toga, Arthur W, Borowski, Bret, Ward, Chad, DeCarli, Charles, Mathis, Chet, Jack, Clifford R, Harvey, Danielle, Holtzman, David, Jones, David, Gessert, Devon, Lilly, Eli, Reiman, Eric M, Franklin, Erin, Hefti, Franz, Sorensen, Greg, Jimenez, Gustavo, Fillit, Howard, Gunter, Jeff, Salazar, Jennifer, Hsiao, John, Morris, John, Trojanowki, John Q, Neu, Karen Crawford Scott, Kantarci, Kejal, Faber, Kelley, Harless, Kelly, Chen, Kewei, Nho, Kwangsik, Beckett, Laurel, Thal, Lean, Thal, Leon, Shaw, Leslie M, Kuller, Lew, Shen, Li, Hergesheimer, Lindsey, Taylor-Reinwald, Lisa, Mesulam, M Marcel, Korecka, Magdalena, Raichle, Marc, Carrillo, Maria, Albert, Marilyn, Senjem, Matt, Bernstein, Matthew, Donohue, Michael, Weiner, Michael, Figurski, Michal, Buckholtz, Neil, Fox, Nick, Cairns, Nigel J, Schuff, Norbert, Foster, Norm, Aisen, Paul, Thompson, Paul, Davies, Peter, Snyder, Peter J, Snyder, Peter, Vemuri, Prashanthi, Frank, Richard, Koeppe, Robert A, Green, Robert C, Petersen, Ronald, Walter, Sarah, Paul, Steven, Potkin, Steven, Kim, Sungeun, Foroud, Tatiana M, Montine, Tom, Lee, Virginia, Jagust, William, Potter, William, Cabrera, Yuliana, Khachaturian, Zaven, Fleisher, Adam, Pierce, Aimee, Mintz, Akiva, Lerner, Alan, Norbash, Alexander, Levey, Allan I, Rosen, Allyson, Smith, Amanda, Ulysse, Anaztasia, Budson, Andrew E, Kertesz, Andrew, Oliver, Angela, Hake, Ann Marie, Burke, Anna, Sarrael, Antero, and Porsteinsson, Anton P

Subjects
Biological Sciences, Genetics, Alzheimer's Disease, Clinical Research, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Human Genome, Neurosciences, Dementia, Acquired Cognitive Impairment, Brain Disorders, Prevention, Neurodegenerative, Aging, 2.1 Biological and endogenous factors, 4.1 Discovery and preclinical testing of markers and technologies, Neurological, Good Health and Well Being, Age of Onset, Aged, Aged, 80 and over, Alzheimer Disease, Apolipoproteins E, Asian People, China, Cohort Studies, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Immune System, Male, Middle Aged, Potassium Channels, Inwardly Rectifying, Risk Factors, Alzheimer’s Disease Neuroimaging Initiative, Alzheimer’s disease, GWAS, immune, risk variant, whole-genome sequencing
Abstract

Alzheimer's disease (AD) is a leading cause of mortality among the elderly. We performed a whole-genome sequencing study of AD in the Chinese population. In addition to the variants identified in or around the APOE locus (sentinel variant rs73052335, P = 1.44 × 10-14), two common variants, GCH1 (rs72713460, P = 4.36 × 10-5) and KCNJ15 (rs928771, P = 3.60 × 10-6), were identified and further verified for their possible risk effects for AD in three small non-Asian AD cohorts. Genotype-phenotype analysis showed that KCNJ15 variant rs928771 affects the onset age of AD, with earlier disease onset in minor allele carriers. In addition, altered expression level of the KCNJ15 transcript can be observed in the blood of AD subjects. Moreover, the risk variants of GCH1 and KCNJ15 are associated with changes in their transcript levels in specific tissues, as well as changes of plasma biomarkers levels in AD subjects. Importantly, network analysis of hippocampus and blood transcriptome datasets suggests that the risk variants in the APOE, GCH1, and KCNJ15 loci might exert their functions through their regulatory effects on immune-related pathways. Taking these data together, we identified common variants of GCH1 and KCNJ15 in the Chinese population that contribute to AD risk. These variants may exert their functional effects through the immune system.

Published
2018

9. Multi-ancestry genome-wide association meta-analysis of Parkinson’s disease

Author

the 23andMe Research Team, the Global Parkinson's Genetics Program (GP2), Ip, Nancy Yuk-yu, Chan, Yin Cheung Phillip, Zhou, Xiaopu, the 23andMe Research Team, the Global Parkinson's Genetics Program (GP2), Ip, Nancy Yuk-yu, Chan, Yin Cheung Phillip, and Zhou, Xiaopu

Abstract

Although over 90 independent risk variants have been identified for Parkinson’s disease using genome-wide association studies, most studies have been performed in just one population at a time. Here we performed a large-scale multi-ancestry meta-analysis of Parkinson’s disease with 49,049 cases, 18,785 proxy cases and 2,458,063 controls including individuals of European, East Asian, Latin American and African ancestry. In a meta-analysis, we identified 78 independent genome-wide significant loci, including 12 potentially novel loci (MTF2, PIK3CA, ADD1, SYBU, IRS2, USP8, PIGL, FASN, MYLK2, USP25, EP300 and PPP6R2) and fine-mapped 6 putative causal variants at 6 known PD loci. By combining our results with publicly available eQTL data, we identified 25 putative risk genes in these novel loci whose expression is associated with PD risk. This work lays the groundwork for future efforts aimed at identifying PD loci in non-European populations.

Published
2024

10. Using blood transcriptome analysis for Alzheimer's disease diagnosis and patient stratification

Author

Zhong, Huan, Zhou, Xiaopu, Uhm, Hyebin, Jiang, Yuanbing, Cao, Han, Chen, Yu, Mak, Tiffany T. W., Lo, Ronnie Ming Nok, Wong, Bonnie Wing Yan, Cheng, Elaine Yee Ling, Mok, Kin Ying Boniface, Chan, Andrew Lung Tat, Kwok, Timothy C. Y., Mok, Vincent C. T., Ip, Fanny Chui Fun, Hardy, John, Fu, Amy Kit Yu, Ip, Nancy Yuk-yu, Zhong, Huan, Zhou, Xiaopu, Uhm, Hyebin, Jiang, Yuanbing, Cao, Han, Chen, Yu, Mak, Tiffany T. W., Lo, Ronnie Ming Nok, Wong, Bonnie Wing Yan, Cheng, Elaine Yee Ling, Mok, Kin Ying Boniface, Chan, Andrew Lung Tat, Kwok, Timothy C. Y., Mok, Vincent C. T., Ip, Fanny Chui Fun, Hardy, John, Fu, Amy Kit Yu, and Ip, Nancy Yuk-yu

Abstract

INTRODUCTION Blood protein biomarkers demonstrate potential for Alzheimer's disease (AD) diagnosis. Limited studies examine the molecular changes in AD blood cells. METHODS Bulk RNA-sequencing of blood cells was performed on AD patients of Chinese descent (n = 214 and 26 in the discovery and validation cohorts, respectively) with normal controls (n = 208 and 38 in the discovery and validation cohorts, respectively). Weighted gene co-expression network analysis (WGCNA) and deconvolution analysis identified AD-associated gene modules and blood cell types. Regression and unsupervised clustering analysis identified AD-associated genes, gene modules, cell types, and established AD classification models. RESULTS WGCNA on differentially expressed genes revealed 15 gene modules, with 6 accurately classifying AD (areas under the receiver operating characteristics curve [auROCs] > 0.90). These modules stratified AD patients into subgroups with distinct disease states. Cell-type deconvolution analysis identified specific blood cell types potentially associated with AD pathogenesis. DISCUSSION This study highlights the potential of blood transcriptome for AD diagnosis, patient stratification, and mechanistic studies. Highlights We comprehensively analyze the blood transcriptomes of a well-characterized Alzheimer's disease cohort to identify genes, gene modules, pathways, and specific blood cells associated with the disease. Blood transcriptome analysis accurately classifies and stratifies patients with Alzheimer's disease, with some gene modules achieving classification accuracy comparable to that of the plasma ATN biomarkers. Immune-associated pathways and immune cells, such as neutrophils, have potential roles in the pathogenesis and progression of Alzheimer's disease.

Published
2024

11. Using blood transcriptome analysis for Alzheimer's disease diagnosis and patient stratification

Author

Zhong, Huan, primary, Zhou, Xiaopu, additional, Uhm, Hyebin, additional, Jiang, Yuanbing, additional, Cao, Han, additional, Chen, Yu, additional, Mak, Tiffany T. W., additional, Lo, Ronnie Ming Nok, additional, Wong, Bonnie Wing Yan, additional, Cheng, Elaine Yee Ling, additional, Mok, Kin Y., additional, Chan, Andrew Lung Tat, additional, Kwok, Timothy C. Y., additional, Mok, Vincent C. T., additional, Ip, Fanny C. F., additional, Hardy, John, additional, Fu, Amy K. Y., additional, and Ip, Nancy Y., additional

Published
2024
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14. Transferability of a European-derived Alzheimer’s Disease Genetic Risk Score across Multi-Ancestry Populations

Author

Nicolas, Aude, primary, Grenier-Boley, Benjamin, additional, Sherva, Richard, additional, Kim, Yoontae, additional, Kikuchi, Masataka, additional, de Rojas, Itziar, additional, Dalmasso, Carolina, additional, Zhou, Xiaopu, additional, Guen, Yann Le, additional, Arboleda-Bustos, Carlos E, additional, Camargos Bicalho, Maria Aparecida, additional, Guerchet, Maëlenn, additional, van der Lee, Sven, additional, Goss, Monica, additional, Castillo, Atahualpa, additional, Bellenguez, Céline, additional, Küçükali, Fahri, additional, Satizabal Barrera, Claudia, additional, Fongang, Bernard, additional, yang, Qiong, additional, Peters, Oliver, additional, Schneider, Anja, additional, Dichgans, Martin, additional, Rujescu, Dan, additional, Scherbaum, Norbert, additional, Deckert, Jürgen, additional, Riedel-Heller, Steffi, additional, Hausner, Lucrezia, additional, Molina Porcel, Laura, additional, Düzel, Emrah, additional, Grimmer, Timo, additional, Wiltfang, Jens, additional, Heilmann-Heimbach, Stefanie, additional, Moebus, Susanne, additional, Tegos, Thomas, additional, Scarmeas, Nikolaos, additional, Dols-Icardo, Oriol, additional, Moreno, Fermin, additional, Pérez-Tur, Jordi, additional, Bullido, María J., additional, Pastor, Pau, additional, Sánchez-Valle, Raquel, additional, Álvarez, Victoria, additional, Cao, Han, additional, Ip, Nancy Y., additional, Fu, Amy K. Y., additional, Ip, Fanny C. F., additional, Olivar, Natividad, additional, Muchnik, Carolina, additional, Cuesta, Carolina, additional, Campanelli, Lorenzo, additional, Solis, Patricia, additional, Politis, Daniel Gustavo, additional, Kochen, Silvia, additional, Brusco, Luis Ignacio, additional, Boada, Mercè, additional, García-González, Pablo, additional, Puerta, Raquel, additional, Mir, Pablo, additional, Real, Luis M, additional, Piñol-Ripoll, Gerard, additional, María García-Alberca, Jose, additional, Luís Royo, Jose, additional, Rodriguez-Rodriguez, Eloy, additional, Soininen, Hilkka, additional, Heikkinen, Sami, additional, de Mendonça, Alexandre, additional, Mehrabian, Shima, additional, Traykov, Latchezar, additional, Hort, Jakub, additional, Vyhnalek, Martin, additional, Rasmussen, Katrine Laura, additional, Qvist Thomassen, Jesper, additional, Pijnenburg, Yolande A.L., additional, Holstege, Henne, additional, van Swieten, John, additional, Ramakers, Inez, additional, Verhey, Frans, additional, van der Lugt, Aad, additional, Scheltens, Philip, additional, Ortega-Rojas, Jenny, additional, Concha Mera, Ana Gabriela, additional, Mahecha, Maria F., additional, Pardo, Rodrogo, additional, Arboleda, Gonzalo, additional, Graff, Caroline, additional, Papenberg, Goran, additional, Giedraitis, Vilmantas, additional, Boland, Anne, additional, Deleuze, Jean-François, additional, Armando de Marco, Luiz, additional, Nunes de Moraes, Edgar, additional, de Viana, Bernardo, additional, Túlio Gualberto Cintra, Marco, additional, Grsiwold, Anthony, additional, Forund, Tatiana, additional, Cruchaga, Carlos, additional, Haines, Jonathan, additional, Farrer, Lindsay, additional, DeStefano, Anita, additional, Wijsman, Ellen, additional, Mayeux, Richard, additional, Pericak-Vance, Margaret, additional, Kunkle, Brian, additional, Goate, Alison, additional, Schellenberg, Gerard D., additional, Vardarajan, Badri, additional, Wang, Li-San, additional, Leung, Yuk Yee, additional, Dalgard, Clifton, additional, Nicolas, Gael, additional, Wallon, David, additional, Dufouil, Carole, additional, Pasquier, Florence, additional, Hanon, Olivier, additional, Debette, Stéphanie, additional, Grünblatt, Edna, additional, Popp, Julius, additional, Angel, Bárbara, additional, Golger, Sergio, additional, Victoria Chacon, Maria, additional, Aranguiz, Rafael, additional, Orellana, Paulina, additional, Slachevsky, Andrea, additional, Gonzalez-Billault, Christian, additional, Albala, Cecilia, additional, Fuentes, Patricio, additional, Porter, Tenielle, additional, Laws, Simon M, additional, Sachdev, Perminder, additional, Mather, Karen, additional, Hauger, Richard L., additional, Merritt, Victoria, additional, Panizzon, Matthew, additional, Zhang, Rui, additional, Gaziano, Michael, additional, Ghidoni, Roberta, additional, Galimberti, Daniela, additional, Arosio, Beatrice, additional, Mecocci, Patrizia, additional, Solfrizzi, Vincenzo, additional, Parnetti, Lucilla, additional, Squassina, Alessio, additional, Tremolizzo, Lucio, additional, Borroni, Barbara, additional, Nacmias, Benedetta, additional, Caffarra, Paolo, additional, Seripa, Davide, additional, Rainero, Innocenzo, additional, Daniele, Antonio, additional, Piras, Fabrizio, additional, Miyashita, Akinori, additional, Hara, Norikazu, additional, Ozaki, Kouichi, additional, Niida, Shumpei, additional, Williams, Julie, additional, Masullo, Carlo, additional, Amouyel, Philippe, additional, Preux, Pierre-Marie, additional, Mbelesso, Pascal, additional, Bandzouzi, Bébène, additional, Saykin, Andy, additional, Jessen, Frank, additional, Kehoe, Patrick, additional, Van Duijn, Cornelia, additional, Gim, Jungsoo, additional, Ben Salem, Nesrine, additional, Frikke-Schmidt, Ruth, additional, Cherni, Lofti, additional, Greicius, Michael D., additional, Tsolaki, Magda, additional, Sánchez-Juan, Pascual, additional, Romano Silva, Marco Aurélio, additional, Sleegers, Kristel, additional, Ingelsson, Martin, additional, Dartigues, Jean-François, additional, Seshadri, Sudha, additional, Rossi, Giacomina, additional, Morelli, Laura, additional, Hiltunen, Mikko, additional, Sims, Rebecca, additional, van der Flier, Wiesje, additional, Andreassen, Ole, additional, Arboleda, Humberto, additional, Escott-Price, Valentina, additional, Ruiz, Agustín, additional, Lee, Kun Ho, additional, Ikeuchi, Takeshi, additional, Ramirez, Alfredo, additional, Logue, Mark, additional, and Lambert, Jean-Charles, additional

Published
2023
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15. Identification of genetic risk loci and causal insights associated with Parkinson's disease in African and African admixed populations: a genome-wide association study

Author

Rizig, Mie, primary, Bandres-Ciga, Sara, additional, Makarious, Mary B, additional, Ojo, Oluwadamilola Omolara, additional, Crea, Peter Wild, additional, Abiodun, Oladunni Victoria, additional, Levine, Kristin S, additional, Abubakar, Sani Atta, additional, Achoru, Charles Obiora, additional, Vitale, Dan, additional, Adeniji, Olaleye Akinmola, additional, Agabi, Osigwe Paul, additional, Koretsky, Mathew J, additional, Agulanna, Uchechi, additional, Hall, Deborah A, additional, Akinyemi, Rufus Olusola, additional, Xie, Tao, additional, Ali, Mohammed Wulgo, additional, Shamim, Ejaz A, additional, Ani-Osheku, Ifeyinwa, additional, Padmanaban, Mahesh, additional, Arigbodi, Ohwotemu Michael, additional, Standaert, David G, additional, Bello, Abiodun Hamzat, additional, Dean, Marissa N, additional, Erameh, Cyril Oshomah, additional, Elsayed, Inas, additional, Farombi, Temitope Hannah, additional, Okunoye, Olaitan, additional, Fawale, Michael Bimbola, additional, Billingsley, Kimberley J, additional, Imarhiagbe, Frank Aiwansoba, additional, Jerez, Pilar Alvarez, additional, Iwuozo, Emmanuel Uzodinma, additional, Baker, Breeana, additional, Komolafe, Morenikeji Adeyoyin, additional, Malik, Laksh, additional, Nwani, Paul Osemeke, additional, Daida, Kensuke, additional, Nwazor, Ernest Okwundu, additional, Miano-Burkhardt, Abigail, additional, Nyandaiti, Yakub Wilberforce, additional, Fang, Zih-Hua, additional, Obiabo, Yahaya Olugbo, additional, Kluss, Jillian H, additional, Odeniyi, Olanike Adedoyin, additional, Hernandez, Dena G, additional, Odiase, Francis Ehidiamen, additional, Tayebi, Nahid, additional, Ojini, Francis Ibe, additional, Sidranksy, Ellen, additional, Onwuegbuzie, Gerald Awele, additional, D'Souza, Andrea M, additional, Osaigbovo, Godwin Osawaru, additional, Berhe, Bahafta, additional, Osemwegie, Nosakhare, additional, Reed, Xylena, additional, Oshinaike, Olajumoke Olufemi, additional, Leonard, Hampton L, additional, Otubogun, Folajimi Morenikeji, additional, Alvarado, Chelsea X, additional, Oyakhire, Shyngle Imiewan, additional, Ozomma, Simon Izuchukwu, additional, Samuel, Sarah Chabiri, additional, Taiwo, Funmilola Tolulope, additional, Wahab, Kolawole Wasiu, additional, Zubair, Yusuf Agboola, additional, Iwaki, Hirotaka, additional, Kim, Jonggeol Jeffrey, additional, Morris, Huw R, additional, Hardy, John, additional, Nalls, Mike A, additional, Heilbron, Karl, additional, Norcliffe-Kaufmann, Lucy, additional, Blauwendraat, Cornelis, additional, Houlden, Henry, additional, Singleton, Andrew, additional, Okubadejo, Njideka Ulunma, additional, Okubadejo, Njideka, additional, Ojo, Oluwadamilola, additional, Abiodun, Oladunni, additional, Achoru, Charles, additional, Agabi, Osigwe, additional, Akinyemi, Rufus, additional, Ali, Mohammed, additional, Arigbodi, Ohwotemu, additional, Bello, Abiodun, additional, Erameh, Cyril, additional, Farombi, Temitope, additional, Fawale, Michael, additional, Imarhiagbe, Frank, additional, Iwuozo, Emmanuel, additional, Komolafe, Morenikeji, additional, Nwani, Paul, additional, Nwazor, Ernest, additional, Nyandaiti, Yakub, additional, Obiabo, Yahaya, additional, Odeniyi, Olanike, additional, Odiase, Francis, additional, Ojini, Francis, additional, Onwuegbuzie, Gerald, additional, Osaigbovo, Godwin, additional, Oshinaike, Olajumoke, additional, Otubogun, Folajimi, additional, Oyakhire, Shyngle, additional, Ozomma, Simon, additional, Samuel, Sarah, additional, Taiwo, Funmilola, additional, Wahab, Kolawole, additional, Zubair, Yusuf, additional, Gams Massi, Daniel, additional, Gueumekane Bila lamou, Eric, additional, Njamnshi Nfor, Leonard, additional, Magnerou, Mélanie Annick, additional, Fogang Fogoum, Yannick, additional, Shalash, Ali, additional, El-FawaI, Hassan, additional, Khedr, Eman, additional, Fawi, Gharib, additional, A. Eltantawi, Mohamed, additional, Salama, Mohamed, additional, El-Jaafary, Shaimaa, additional, Hamed, Sharifa, additional, Tafesse Mengesha, Abenet, additional, Alemayehu Ayele, Biniyam, additional, Melka Oda, Dereje, additional, Zenebe Zewde, Yared, additional, Debebe Gelan, Yohanesse, additional, AkpaIu, Albert, additional, Charway-Felli, Augustina, additional, Stephen Sarfo, Fred, additional, Adjei, Patrick, additional, Obese, Vida, additional, Bocoum, Abdoulaye, additional, Koita, Abdou, additional, Oumar Guinto, Cheick, additional, Coulibaly, Toumany, additional, Maiga, Youssoufa, additional, Kone, Zaynab, additional, Bell, Abiodun, additional, Adebowale, Akintunde A., additional, Akpekpe, John, additional, lyagba, Alagoma, additional, Wulgo, Ali Mohammed, additional, Arabambi, Babawale, additional, Agu, Christian, additional, Dike, Franklin, additional, Ishola, Ismail, additional, Abiodun, Kehinde, additional, Ekenze, Oluchi, additional, Agabi Osigwe, Paul, additional, Balarabe, Salisu, additional, Abubakar, Sani, additional, Williams, Uduak, additional, Fall, Maouly, additional, Mamadou Diop, Alassane, additional, Hilaire Dominique, Ewodo Touna, additional, Mochan, Andre, additional, Modi, Girish, additional, Dindayal, Saiesha, additional, Ali Awadelkareem, Eman, additional, Dahawi, Maha, additional, Awadelkareem, Mosab Ali, additional, Misbah, Sarah, additional, Mushengez, Brighton, additional, Kimambo, Henrika, additional, Msango, Leonard, additional, Adebayo, Philip, additional, OKeng, Kigocha, additional, Diekker, Marieke, additional, URassa, Sarah, additional, Gouider, Riadh, additional, Ben Djebara, Mouna, additional, Gargouri, Amina, additional, Kacem, Imen, additional, Nasri, Amina, additional, Mrabet, Saloua, additional, Sghaier, Ikram, additional, Mkada, Imen, additional, Atadzhanov, Masharip, additional, Chishimba, Lorraine, additional, Rizig, Mie, additional, Jama, Fatumah, additional, Nalls, Mike, additional, Shamim, Ejaz, additional, Jonas, Cabell, additional, Williamson, Jared, additional, Hall, Deborah A., additional, Rosenbaum, Marc, additional, Davis, Staci, additional, Dean, Marissa, additional, Cromer, Candace, additional, Smith, Jenna, additional, Ruffrage, Lauren, additional, Richardson, Joseph, additional, Sipma, Rebeka, additional, Padmanaban, Manesh, additional, Warren, Natalie, additional, Mercado, Tomas, additional, Disbrow, Elizabeth, additional, Chauppeta, Brian, additional, Thomas-Dean, Fermine, additional, Toms, Jamie, additional, Lofton, Katelyn, additional, Rawls, Ashley, additional, Rizer, Kyle, additional, Black, Nieci, additional, Solle, Justin, additional, O'Grady, Alyssa, additional, Sherer, Todd, additional, Fiske, Brian, additional, Başak, A. Nazlı, additional, Tan, Ai Huey, additional, Noyce, Alastair, additional, Akpalu, Albert, additional, Espay, Alberto, additional, Martínez-Carrasco, Alejandro, additional, Medina, Alex, additional, Zimprich, Alexander, additional, Brice, Alexis, additional, Karimova, Altynay, additional, Hernandez, Alvaro, additional, Illarionova, Anastasia, additional, Quattrone, Andrea, additional, Singleton, Andrew B, additional, Sobering, Andrew K., additional, Vinuela, Angel, additional, Sanyaolu, Arinola, additional, Schumacher-Schuh, Artur F., additional, Kishore, Asha, additional, Ahmad-Annuar, Azlina, additional, Al Mubarak, Bashayer, additional, Tang, Beisha, additional, Pizarro Galleguillos, Benjamin, additional, Jeon, Beomseok, additional, Siddiqi, Bernadette, additional, Casey, Bradford, additional, Mollenhauer, Brit, additional, Carroll, Camille, additional, Rieder, Carlos, additional, Pantazis, Caroline B., additional, Comart, Charisse, additional, Lin, Chin-Hsien, additional, Klein, Christine, additional, Bale, Claire, additional, Shepherd, Claire E, additional, Wegel, Claire, additional, Martinez-Ramirez, Daniel, additional, Hall, Deborah, additional, Hernandez, Dena, additional, KP, Divya, additional, Nguyen, Duan, additional, Fon, Edward A., additional, Dadiotis, Efthymios, additional, Riley, Ekemini, additional, Iakovenko, Elena, additional, Stafford, Ellie, additional, Gatto, Emilia M, additional, Valente, Enza Maria, additional, Vollstedt, Eva-Juliane, additional, Faghri, Faraz, additional, Genc, Gencer, additional, Xiromerisiou, Georgia, additional, Hadjigorgiou, Georgios, additional, Hiu-Fai Chan, Germaine, additional, Arboleda, Gonzalo, additional, Kaishibayeva, Gulnaz, additional, Höglinger, Günter, additional, Leonard, Hampton, additional, Madoev, Harutyun, additional, Chen, Honglei, additional, Wu, Hsiu-Chuan, additional, Shang, Huifang, additional, F. Mata, Ignacio, additional, Keller Sarmiento, Ignacio Juan, additional, Dagklis, Ioannis, additional, Tarnanas, Ioannis, additional, Aasly, Jan O., additional, Hoenicka, Janet, additional, Corvol, Jean-Christophe, additional, Foo, Jia Nee, additional, Guo, Jifeng, additional, Junker, Johanna, additional, Carr, Jonathan, additional, Kim, Jonggeol Jeff, additional, Orozco, Jorge, additional, Jankovic, Joseph, additional, Shulman, Joshua, additional, Hunter, Julie, additional, Solle, Justin C., additional, Murphy, Kaileigh, additional, Nuytemans, Karen, additional, Kieburtz, Karl, additional, Lohmann, Katja, additional, Marek, Kenneth, additional, Mok, Kin Ying, additional, Kumar, Kishore, additional, Levine, Kristin, additional, Chahine, Lana M., additional, Lange, Lara M., additional, Pihlstrøm, Lasse, additional, Screven, Laurel, additional, Stefanis, Leonidas, additional, Shulman, Lisa, additional, Marsili, Luca, additional, Parnetti, Lucilla, additional, Kuhl, Maggie, additional, Funayama, Manabu, additional, Sharma, Manu, additional, Tan, Manuela, additional, Kauffman, Marcelo, additional, Miranda, Marcelo, additional, Bustamante, Maria Leonor, additional, Stamelou, Maria, additional, Periñan Tocino, Maria Teresa, additional, Cornejo-Olivas, Mario, additional, Jimenez del Rio, Marlene, additional, Koretsky, Mathew, additional, Rodriguez-Violante, Mayela, additional, Ellis, Melina, additional, Avenali, Micol, additional, Rentería, Miguel E., additional, Inca-Martines, Miguel z, additional, Nalls, Mike A., additional, Ibrahim Norlinah, Mohamed, additional, Umair, Muhammad, additional, Ip, Nancy, additional, Louie, Naomi, additional, Cheung, Nelson Yuk-Fai, additional, Mencacci, Niccolò Emanuele, additional, Wood, Nicholas, additional, Williams, Nigel, additional, Hattori, Nobutaka, additional, Abdul Murad, Nor Azian, additional, Ibrahim, Norlinah Mohamed, additional, Monchi, Oury, additional, Öztop Çakmak, Özgür, additional, Öztop Çakmak, Patricio Öztop Çakmak, additional, Lewis, Patrick Alfryn, additional, Pastor, Pau, additional, Reyes-Pérez, Paula, additional, Saffie Awad, Paula, additional, Chana, Pedro, additional, Chan, Phillip, additional, Kung, Pin-Jui, additional, Chan, Piu, additional, Pal, Pramod, additional, Lingappa Kukkle, Prashanth, additional, Ojha, Rajeev, additional, Kaiyrzhanov, Rauan, additional, Krüger, Rejko, additional, Amouri, Rim, additional, Weil, Rimona, additional, Rajan, Roopa, additional, Alcalay, Roy, additional, Wu, Ruey-Meei, additional, Borgohain, Rupam, additional, Sassi, Samia Ben, additional, Khachatryan, Samson, additional, El-Sadig, Sarah, additional, Wu, Serena, additional, Groppa, Sergio, additional, Azmin, Shahrul, additional, Lim, Shen-Yang, additional, Ur-Rehman, Shoaib, additional, Ertan, Sibel, additional, Stott, Simon, additional, Jasaitye, Simona, additional, Chowdhury, Sohini, additional, Dumanis, Sonya, additional, Bardien, Soraya, additional, Lubbe, Steven, additional, Koks, Sulev, additional, Dey, Sumit, additional, Foroud, Tatiana, additional, Fon, Ted, additional, Beach, Thomas, additional, Gasser, Thomas, additional, Anderson, Tim, additional, Nguyen, Toan, additional, Schirinzi, Tommaso, additional, Shiraishi, Tomotaka, additional, Pitcher, Toni, additional, Tumas, Vitor, additional, Mohamed, Wael, additional, Kamel, Walaa A., additional, Luo, Wei, additional, Zhou, Xiaopu, additional, Zewde, Yared Z., additional, Song, Yeajin, additional, Wen, Yi, additional, Wu, Yihru, additional, Joong Kim, Yun, additional, and Tavadyan, Zaruhi, additional

Published
2023
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17. Author Correction: Elucidating causative gene variants in hereditary Parkinson’s disease in the Global Parkinson’s Genetics Program (GP2)

Author

Global Parkinson’s Genetic Program (GP2), Ip, Nancy Yuk-yu, Chan, Yin Cheung Phillip, Zhou, Xiaopu, Global Parkinson’s Genetic Program (GP2), Ip, Nancy Yuk-yu, Chan, Yin Cheung Phillip, and Zhou, Xiaopu

Abstract

Correction to: npj Parkinson’s Disease https://doi.org/10.1038/s41531-023-00526-9, published online 27 June 2023 In this article the Global Parkinson’s Genetics Program (GP2) members names and affiliations were missing in the main author list of the Original article which are listed in the below.

Published
2023

18. Elucidating causative gene variants in hereditary Parkinson’s disease in the Global Parkinson’s Genetics Program (GP2)

Author

Global Parkinson’s Genetic Program (GP2), Ip, Nancy Yuk-yu, Chan, Yin Cheung Phillip, Zhou, Xiaopu, Global Parkinson’s Genetic Program (GP2), Ip, Nancy Yuk-yu, Chan, Yin Cheung Phillip, and Zhou, Xiaopu

Abstract

The Monogenic Network of the Global Parkinson’s Genetics Program (GP2) aims to create an efficient infrastructure to accelerate the identification of novel genetic causes of Parkinson’s disease (PD) and to improve our understanding of already identified genetic causes, such as reduced penetrance and variable clinical expressivity of known disease-causing variants. We aim to perform short- and long-read whole-genome sequencing for up to 10,000 patients with parkinsonism. Important features of this project are global involvement and focusing on historically underrepresented populations.

Published
2023

19. Defining the causes of sporadic Parkinson’s disease in the global Parkinson’s genetics program (GP2)

Author

the Global Parkinson’s Genetics Program (GP2), Towns, Clodagh, Morris, Huw R, Ip, Nancy Yuk-yu, Chan, Philip, Zhou, Xiaopu, the Global Parkinson’s Genetics Program (GP2), Towns, Clodagh, Morris, Huw R, Ip, Nancy Yuk-yu, Chan, Philip, and Zhou, Xiaopu

Abstract

The Global Parkinson’s Genetics Program (GP2) will genotype over 150,000 participants from around the world, and integrate genetic and clinical data for use in large-scale analyses to dramatically expand our understanding of the genetic architecture of PD. This report details the workflow for cohort integration into the complex arm of GP2, and together with our outline of the monogenic hub in a companion paper, provides a generalizable blueprint for establishing large scale collaborative research consortia.

Published
2023

20. Compositions, Methods and Kits for Detection of Genetic Variants for Alzheimer's Disease

Author

Ip, Nancy Yuk-yu, Fu, Kit Yu, Chen, Yu, Zhou, Xiaopu, Ip, Nancy Yuk-yu, Fu, Kit Yu, Chen, Yu, and Zhou, Xiaopu

Abstract

Provided herein are methods, kits, and devices related to genetic variations of neurological disorders. For example, methods, kits, and devices for using such genetic variations to assess susceptibility of developing Alzheimer’s disease.

Published
2023

21. Deep learning-based polygenic risk analysis for Alzheimer’s disease prediction

Author

Alzheimer’s Disease Neuroimaging Initiative, Zhou, Xiaopu, Chen, Yu, Ip, Fanny Chui Fun, Jiang, Yuanbing, Cao, Han, Lv, Ge, Zhang, Huan, Chen, Jiahang, Ye, Tao, Chen, Yuewen, Zhang, Yulin, Ma, Shuangshuang, Lo, Ronnie M.N., Tong, Pui Sze, Mok, Vincent C.T., Kwok, Timothy C.Y., Guo, Qihao, Mok, Kin Ying Boniface, Shoai, Maryam, Hardy, John, Chen, Lei, Fu, Kit Yu, Ip, Nancy Yuk-yu, Alzheimer’s Disease Neuroimaging Initiative, Zhou, Xiaopu, Chen, Yu, Ip, Fanny Chui Fun, Jiang, Yuanbing, Cao, Han, Lv, Ge, Zhang, Huan, Chen, Jiahang, Ye, Tao, Chen, Yuewen, Zhang, Yulin, Ma, Shuangshuang, Lo, Ronnie M.N., Tong, Pui Sze, Mok, Vincent C.T., Kwok, Timothy C.Y., Guo, Qihao, Mok, Kin Ying Boniface, Shoai, Maryam, Hardy, John, Chen, Lei, Fu, Kit Yu, and Ip, Nancy Yuk-yu

Abstract

[Background] The polygenic nature of Alzheimer’s disease (AD) suggests that multiple variants jointly contribute to disease susceptibility. As an individual’s genetic variants are constant throughout life, evaluating the combined effects of multiple disease-associated genetic risks enables reliable AD risk prediction. Because of the complexity of genomic data, current statistical analyses cannot comprehensively capture the polygenic risk of AD, resulting in unsatisfactory disease risk prediction. However, deep learning methods, which capture nonlinearity within high-dimensional genomic data, may enable more accurate disease risk prediction and improve our understanding of AD etiology. Accordingly, we developed deep learning neural network models for modeling AD polygenic risk. [Methods] We constructed neural network models to model AD polygenic risk and compared them with the widely used weighted polygenic risk score and lasso models. We conducted robust linear regression analysis to investigate the relationship between the AD polygenic risk derived from deep learning methods and AD endophenotypes (i.e., plasma biomarkers and individual cognitive performance). We stratified individuals by applying unsupervised clustering to the outputs from the hidden layers of the neural network model. [Results] The deep learning models outperform other statistical models for modeling AD risk. Moreover, the polygenic risk derived from the deep learning models enables the identification of disease-associated biological pathways and the stratification of individuals according to distinct pathological mechanisms. [Conclusion] Our results suggest that deep learning methods are effective for modeling the genetic risks of AD and other diseases, classifying disease risks, and uncovering disease mechanisms.

Published
2023

25. Multi‐Omics‐Based Autophagy‐Related Untypical Subtypes in Patients with Cerebral Amyloid Pathology

Author

Park, Jong‐Chan, primary, Barahona‐Torres, Natalia, additional, Jang, So‐Yeong, additional, Mok, Kin Y., additional, Kim, Haeng Jun, additional, Han, Sun‐Ho, additional, Cho, Kwang‐Hyun, additional, Zhou, Xiaopu, additional, Fu, Amy K. Y., additional, Ip, Nancy Y., additional, Seo, Jieun, additional, Choi, Murim, additional, Jeong, Hyobin, additional, Hwang, Daehee, additional, Lee, Dong Young, additional, Byun, Min Soo, additional, Yi, Dahyun, additional, Han, Jong Won, additional, Mook‐Jung, Inhee, additional, and Hardy, John, additional

Published
2022
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26. Demographics and Medication Use of Patients with Late-Onset Alzheimer’s Disease in Hong Kong

Author

Wong, Hiu Yi, Zhong, Huan, Zhou, Xiaopu, Chan, Phillip Y.C., Kwok, Timothy C.Y., Mok, Kin, Hardy, John, Ip, Fanny Chui Fun, Fu, Kit Yu, Ip, Nancy Yuk-yu, Wong, Hiu Yi, Zhong, Huan, Zhou, Xiaopu, Chan, Phillip Y.C., Kwok, Timothy C.Y., Mok, Kin, Hardy, John, Ip, Fanny Chui Fun, Fu, Kit Yu, and Ip, Nancy Yuk-yu

Abstract

Background: Alzheimer’s disease (AD) is the most common cause of dementia in the elderly population. However, epidemiological studies on the demographics of AD in Hong Kong population are lacking. Objective: We investigated the demographics, comorbidities, mortality rates, and medication use of patients with AD in Hong Kong to understand how the disease has been managed locally. Methods: This was a collaborative study of The Hong Kong University of Science and Technology and the Hospital Authority Data Collaboration Lab. We analyzed the demographic data, clinical records, diagnoses, and medication records of patients with AD under the care of the Hospital Authority between January 1, 2007 and December 31, 2017. Results: We identified 23,467 patients diagnosed with AD. The median age at diagnosis was 84 years old, and 71% of patients were female. The most common comorbidity was hypertension (52.6%). 39.9% of patients received medications for dementia; of those, 68.4% had taken those medications for > 1 year. Compared to nonusers, long-term AD medication users had a significantly younger age of AD onset and were taking more lipid-regulating medication, diabetes medication, or antidepressants. Surprisingly, the use of antipsychotics in patients with AD was quite common; 50.7% of patients had received any type of antipsychotic during disease progression. Conclusion: This study provides detailed information on the demographics and medication use of patients with AD in Hong Kong. The data from this AD cohort will aid our future research aiming to identify potential AD risk factors and associations between AD and other diseases.

Published
2022

27. Large-scale plasma proteomic profiling identifies a high-performance biomarker panel for Alzheimer's disease screening and staging

Author

Jiang, Yuanbing, Zhou, Xiaopu, Ip, Fanny Chui Fun, Chan, Philip, Chen, Yu, Lai, Nicole C. H., Cheung, Kit, Lo, Ronnie M. N., Tong, Pui Sze, Wong, Bonnie W. Y., Chan, Andrew L. T., Mok, Vincent C. T., Kwok, Timothy C. Y., Mok, Kin Ying Boniface, Hardy, John, Zetterberg, Henrik, Fu, Kit Yu, Ip, Nancy Yuk-yu, Jiang, Yuanbing, Zhou, Xiaopu, Ip, Fanny Chui Fun, Chan, Philip, Chen, Yu, Lai, Nicole C. H., Cheung, Kit, Lo, Ronnie M. N., Tong, Pui Sze, Wong, Bonnie W. Y., Chan, Andrew L. T., Mok, Vincent C. T., Kwok, Timothy C. Y., Mok, Kin Ying Boniface, Hardy, John, Zetterberg, Henrik, Fu, Kit Yu, and Ip, Nancy Yuk-yu

Abstract

Introduction: Blood proteins are emerging as candidate biomarkers for Alzheimer's disease (AD). We systematically profiled the plasma proteome to identify novel AD blood biomarkers and develop a high-performance, blood-based test for AD. Methods: We quantified 1160 plasma proteins in a Hong Kong Chinese cohort by high-throughput proximity extension assay and validated the results in an independent cohort. In subgroup analyses, plasma biomarkers for amyloid, tau, phosphorylated tau, and neurodegeneration were used as endophenotypes of AD. Results: We identified 429 proteins that were dysregulated in AD plasma. We selected 19 “hub proteins” representative of the AD plasma protein profile, which formed the basis of a scoring system that accurately classified clinical AD (area under the curve = 0.9690–0.9816) and associated endophenotypes. Moreover, specific hub proteins exhibit disease stage-dependent dysregulation, which can delineate AD stages. Discussion: This study comprehensively profiled the AD plasma proteome and serves as a foundation for a high-performance, blood-based test for clinical AD screening and staging. © 2021 the Alzheimer's Association

Published
2022

30. The East Asian Parkinson Disease Genomics Consortium

Author

Mok, Kin Y, primary, Guo, Ji-Feng, additional, Tang, Bei-Sha, additional, Shang, Huifeng, additional, Li, Chunyu, additional, Nguyen, Huong Thi Thanh, additional, Vu, Thi Thanh Huyen, additional, Nguyen, Anh Tuan, additional, Ip, Nancy Y, additional, Fu, Amy KY, additional, Ip, Fanny CF, additional, Zhou, Xiaopu, additional, Cao, Han, additional, Mok, Kin Ying, additional, Hardy, John, additional, Chan, Germaine Hiu Fai, additional, Cheung, Nelson Yuk-Fai, additional, Chan, Phillip, additional, Fong, Wing Chi, additional, Ibrahim, Norlinah Mohamed, additional, Azmin, Shahrul, additional, Abdul Murad, Nor Azian, additional, Sulaiman, Siti Aishah, additional, Desa, Siti Hajar Md, additional, Mohamed, Wael, additional, Koks, Sulev, additional, Pfaff, Abigail, additional, Singleton, Lewis, additional, Kim, Yun Joong, additional, Chung, Seok Jong, additional, Choi, Seong-Min, additional, Chen, Yu, additional, Chen, Yuewen, additional, Ye, Tao, additional, Wu, Yih-Ru, additional, Wu, Hsiu-Chuan, additional, Wu, Ruey-Meei, additional, Lin, Chin-Hsein, additional, Su, Yu-An, additional, Tsai, Mong-Hsun, additional, Shiraishi, Tomotaka, additional, Murakami, Hidetomo, additional, Sengoku, Renpei, additional, Hattori, Nobutaka, additional, Funayama, Manabu, additional, Toda, Tatsushi, additional, Satake, Wataru, additional, Ogaki, Kotaro, additional, Nishioka, Kenya, additional, Singleton, Andrew, additional, Nalls, Mike, additional, and Blauwendraat, Cornelis, additional

Published
2021
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31. A high‐performance biomarker panel for Alzheimer’s disease screening and staging identified by large‐scale plasma proteomic profiling

Author

Jiang, Yuanbing, primary, Zhou, Xiaopu, additional, Ip, Fanny C.F., additional, Chan, Philip, additional, Chen, Yu, additional, Lai, Nicole Chit Hang, additional, Cheung, Kit, additional, Lo, Ronnie M.N., additional, Tong, Estella Pui‐Sze, additional, Wong, Bonnie W.Y., additional, Chan, Andrew L.T., additional, Mok, Vincent C.T., additional, Kwok, Timothy C.Y., additional, Mok, Kin Y., additional, Hardy, John, additional, Zetterberg, Henrik, additional, Fu, Amy K.Y., additional, and Ip, Nancy Y., additional

Published
2021
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32. Deep learning methods improve polygenic risk analysis and prediction for Alzheimer’s disease

Author

Zhou, Xiaopu, primary, Chen, Yu, additional, Ip, Fanny, additional, Jiang, Yuanbing, additional, Cao, Han, additional, Zhong, Huan, additional, Chen, Jiahang, additional, Ye, Tao, additional, Chen, Yuewen, additional, Zhang, Yulin, additional, Ma, Shuangshuang, additional, Lo, Ronnie, additional, Tong, Estella, additional, Initiative, Alzheimer’s Disease Neuroimaging Initiative Alzheimer’s Dise, additional, Mok, Vincent, additional, Kwok, Timothy, additional, Guo, Qihao, additional, Mok, Kin, additional, Shoai, Maryam, additional, Hardy, John, additional, Chen, Lei, additional, Fu, Amy, additional, and Ip, Nancy, additional

Published
2021
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34. GSAP regulates lipid homeostasis and mitochondrial function associated with Alzheimer’s disease

Author

Xu, Peng, primary, Chang, Jerry C., additional, Zhou, Xiaopu, additional, Wang, Wei, additional, Bamkole, Michael, additional, Wong, Eitan, additional, Bettayeb, Karima, additional, Jiang, Lu-Lin, additional, Huang, Timothy, additional, Luo, Wenjie, additional, Xu, Huaxi, additional, Nairn, Angus C., additional, Flajolet, Marc, additional, Ip, Nancy Y., additional, Li, Yue-Ming, additional, and Greengard, Paul, additional

Published
2021
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35. GSAP regulates lipid homeostasis and mitochondrial function associated with Alzheimer's disease

Author

Xu, Peng, Chang, Jerry C., Zhou, Xiaopu, Wang, Wei, Bamkole, Michael, Wong, Eitan, Bettayeb, Karima, Jiang, Lu-Lin, Huang, Timothy, Luo, Wenjie, Xu, Huaxi, Nairn, Angus C., Flajolet, Marc, Ip, Nancy Yuk-yu, Li, Yue-Ming, Greengard, Paul, Xu, Peng, Chang, Jerry C., Zhou, Xiaopu, Wang, Wei, Bamkole, Michael, Wong, Eitan, Bettayeb, Karima, Jiang, Lu-Lin, Huang, Timothy, Luo, Wenjie, Xu, Huaxi, Nairn, Angus C., Flajolet, Marc, Ip, Nancy Yuk-yu, Li, Yue-Ming, and Greengard, Paul

Abstract

Biochemical, pathogenic, and human genetic data confirm that GSAP (γ-secretase activating protein), a selective γ-secretase modulatory protein, plays important roles in Alzheimer's disease (AD) and Down's syndrome. However, the molecular mechanism(s) underlying GSAP-dependent pathogenesis remains largely elusive. Here, through unbiased proteomics and single-nuclei RNAseq, we identified that GSAP regulates multiple biological pathways, including protein phosphorylation, trafficking, lipid metabolism, and mitochondrial function. We demonstrated that GSAP physically interacts with the Fe65-APP complex to regulate APP trafficking/partitioning. GSAP is enriched in the mitochondria-associated membrane (MAM) and regulates lipid homeostasis through the amyloidogenic processing of APP. GSAP deletion generates a lipid environment unfavorable for AD pathogenesis, leading to improved mitochondrial function and the rescue of cognitive deficits in an AD mouse model. Finally, we identified a novel GSAP single-nucleotide polymorphism that regulates its brain transcript level and is associated with an increased AD risk. Together, our findings indicate that GSAP impairs mitochondrial function through its MAM localization and that lowering GSAP expression reduces pathological effects associated with AD.

Published
2021

36. Brain-wide Cas9-mediated cleavage of a gene causing familial Alzheimer’s disease alleviates amyloid-related pathologies in mice

Author

Duan, Yangyang, Ye, Tao, Qu, Zhe, Chen, Yuewen, Miranda, Abigail, Zhou, Xiaopu, Lok, Ka-Chun, Chen, Yu, Fu, Amy K. Y., Gradinaru, Viviana, Ip, Nancy Y., Duan, Yangyang, Ye, Tao, Qu, Zhe, Chen, Yuewen, Miranda, Abigail, Zhou, Xiaopu, Lok, Ka-Chun, Chen, Yu, Fu, Amy K. Y., Gradinaru, Viviana, and Ip, Nancy Y.

Abstract

The pathology of familial Alzheimer’s disease, which is caused by dominant mutations in the gene that encodes amyloid-beta precursor protein (APP) and in those that encode presenilin 1 and presenilin 2, is characterized by extracellular amyloid plaques and intracellular neurofibrillary tangles in multiple brain regions. Here we show that the brain-wide selective disruption of a mutated APP allele in transgenic mouse models carrying the human APP Swedish mutation alleviates amyloid-beta-associated pathologies for at least six months after a single intrahippocampal administration of an adeno-associated virus that encodes both Cas9 and a single-guide RNA that targets the mutation. We also show that the deposition of amyloid-beta, as well as microgliosis, neurite dystrophy and the impairment of cognitive performance, can all be ameliorated when the CRISPR–Cas9 construct is delivered intravenously via a modified adeno-associated virus that can cross the blood–brain barrier. Brain-wide disease-modifying genome editing could represent a viable strategy for the treatment of familial Alzheimer’s disease and other monogenic diseases that affect multiple brain regions.

Published
2021

37. Deep learning for polygenic score analysis for Alzheimer’s disease risk prediction in the Chinese population

Author

Zhou, Xiaopu, Chen, Yu, Ip, Fanny Chui Fun, Jiang, Yuanbing, Cao, Han, Zhong, Huan, Chen, Yuewen, Chen, Jiahang, Zhang, Yulin, Ma, Shuangshuang, Lai, Chit Hang, Lo, Ming Nok, Cheung, Kit, Tong, Pui Sze, Mok, Kin Ying Boniface, Hardy, John, Guo, Qihao, Mok, Vincent C. T., Kwok, Timothy C. Y., Chen, Lei, Fu, Kit Yu, Ip, Nancy Yuk-Yu, Zhou, Xiaopu, Chen, Yu, Ip, Fanny Chui Fun, Jiang, Yuanbing, Cao, Han, Zhong, Huan, Chen, Yuewen, Chen, Jiahang, Zhang, Yulin, Ma, Shuangshuang, Lai, Chit Hang, Lo, Ming Nok, Cheung, Kit, Tong, Pui Sze, Mok, Kin Ying Boniface, Hardy, John, Guo, Qihao, Mok, Vincent C. T., Kwok, Timothy C. Y., Chen, Lei, Fu, Kit Yu, and Ip, Nancy Yuk-Yu

Published
2021

38. Large-scale plasma proteomic profiling identifies a high-performance biomarker panel for Alzheimer's disease screening and staging

Author

Jiang, Yuanbing, Zhou, Xiaopu, Ip, Fanny Chui Fun, Chan, Philip, Chen, Yu, Lai, Nicole C. H., Cheung, Kit, Lo, Ronnie M. N., Tong, Pui Sze, Wong, Bonnie W. Y., Chan, Andrew L. T., Mok, Vincent C. T., Kwok, Timothy C. Y., Mok, Kin Ying Boniface, Hardy, John, Zetterberg, Henrik, Fu, Kit Yu, Ip, Nancy Yuk-yu, Jiang, Yuanbing, Zhou, Xiaopu, Ip, Fanny Chui Fun, Chan, Philip, Chen, Yu, Lai, Nicole C. H., Cheung, Kit, Lo, Ronnie M. N., Tong, Pui Sze, Wong, Bonnie W. Y., Chan, Andrew L. T., Mok, Vincent C. T., Kwok, Timothy C. Y., Mok, Kin Ying Boniface, Hardy, John, Zetterberg, Henrik, Fu, Kit Yu, and Ip, Nancy Yuk-yu

Abstract

Introduction: Blood proteins are emerging as candidate biomarkers for Alzheimer's disease (AD). We systematically profiled the plasma proteome to identify novel AD blood biomarkers and develop a high-performance, blood-based test for AD. Methods: We quantified 1160 plasma proteins in a Hong Kong Chinese cohort by high-throughput proximity extension assay and validated the results in an independent cohort. In subgroup analyses, plasma biomarkers for amyloid, tau, phosphorylated tau, and neurodegeneration were used as endophenotypes of AD. Results: We identified 429 proteins that were dysregulated in AD plasma. We selected 19 “hub proteins” representative of the AD plasma protein profile, which formed the basis of a scoring system that accurately classified clinical AD (area under the curve = 0.9690–0.9816) and associated endophenotypes. Moreover, specific hub proteins exhibit disease stage-dependent dysregulation, which can delineate AD stages. Discussion: This study comprehensively profiled the AD plasma proteome and serves as a foundation for a high-performance, blood-based test for clinical AD screening and staging. © 2021 the Alzheimer's Association

Published
2021

39. Polygenic Score Models For Alzheimer’s Disease: From Research To Clinical Applications

Author

Zhou, Xiaopu, Li, Yolanda Yuen Tung, Fu, Amy Kit Yu, Ip, Nancy Yuk-yu, Zhou, Xiaopu, Li, Yolanda Yuen Tung, Fu, Amy Kit Yu, and Ip, Nancy Yuk-yu

Abstract

The high prevalence of Alzheimer’s disease (AD) among the elderly population and its lack of effective treatments make this disease a critical threat to human health. Recent epidemiological and genetics studies have revealed the polygenic nature of the disease, which is possibly explainable by a polygenic score model that considers multiple genetic risks. Here, we systemically review the rationale and methods used to construct polygenic score models for studying AD. We also discuss the associations of polygenic risk scores (PRSs) with clinical outcomes, brain imaging findings, and biochemical biomarkers from both the brain and peripheral system. Finally, we discuss the possibility of incorporating polygenic score models into research and clinical practice along with potential challenges.

Published
2021

40. A high-performance biomarker panel for Alzheimer's disease screening and staging identified by large-scale plasma proteomic profiling

Author

Jiang, Yuanbing, Zhou, Xiaopu, Ip, Fanny Chui Fun, Chan, Philip, Chen, Yu, Lai, Chit Hang, Cheung, Kit, Lo, Ming Nok, Tong, Pui Sze, Wong, Wing Yan, Chan, Andrew L.T., Mok, Vincent C.T., Kwok, Timothy C.Y., Mok, Kin Ying Boniface, Hardy, John, Zetterberg, Henrik, Fu, Kit Yu, Ip, Nancy Yuk-Yu, Jiang, Yuanbing, Zhou, Xiaopu, Ip, Fanny Chui Fun, Chan, Philip, Chen, Yu, Lai, Chit Hang, Cheung, Kit, Lo, Ming Nok, Tong, Pui Sze, Wong, Wing Yan, Chan, Andrew L.T., Mok, Vincent C.T., Kwok, Timothy C.Y., Mok, Kin Ying Boniface, Hardy, John, Zetterberg, Henrik, Fu, Kit Yu, and Ip, Nancy Yuk-Yu

Abstract

Background Blood proteins are emerging candidate biomarkers for Alzheimer’s disease (AD). A comprehensive investigation of the AD blood proteome will help identify additional biomarkers to delineate the disease’s pathways and define specific AD stages. Method We quantified 1,160 plasma proteins in a Hong Kong Chinese cohort (n = 106 AD patients, n = 74 healthy controls) by high-throughput proximity extension assay to identify AD-associated plasma proteins. Result Plasma proteins involved in diverse biological processes were found to be dysregulated in AD. A subset of plasma proteins was selected to represent the AD plasma protein profile, which formed the basis of a scoring system that can accurately classify AD and associated endophenotypes. In addition, we showed that certain plasma proteins and biological processes exhibit stage-specific dysregulation in AD, thus adding biological annotations to AD stages. Conclusion This study comprehensively profiled the AD plasma proteome and serves as a foundation for a high-performance, blood-based test for clinical AD screening and staging.

Published
2021

41. Large‐scale plasma proteomic profiling identifies a high‐performance biomarker panel for Alzheimer's disease screening and staging

Author

Jiang, Yuanbing, primary, Zhou, Xiaopu, additional, Ip, Fanny C., additional, Chan, Philip, additional, Chen, Yu, additional, Lai, Nicole C.H., additional, Cheung, Kit, additional, Lo, Ronnie M.N., additional, Tong, Estella P.S., additional, Wong, Bonnie W.Y., additional, Chan, Andrew L.T., additional, Mok, Vincent C.T., additional, Kwok, Timothy C.Y., additional, Mok, Kin Y., additional, Hardy, John, additional, Zetterberg, Henrik, additional, Fu, Amy K.Y., additional, and Ip, Nancy Y., additional

Published
2021
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43. Evaluation of genetic risk for Alzheimer’s disease in the Hong Kong Chinese population

Author

Zhou, Xiaopu, primary, Chen, Yu, additional, Lai, Nicole Chit Hang, additional, Li, Yuen Tung, additional, Kwok, Timothy C.Y., additional, Mok, Vincent C.T., additional, Zhang, Yulin, additional, Ma, Shuangshuang, additional, Liu, Saijuan, additional, Chen, Yuewen, additional, Tong, Estella Pui‐Sze, additional, Ip, Fanny C.F., additional, Mok, Kin Y., additional, Hardy, John, additional, Fu, Amy K.Y., additional, and Ip, Nancy Y., additional

Published
2020
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44. GSAP regulates mitochondrial function through the Mitochondria-associated ER membrane in the pathogenesis of Alzheimer’s disease

Author

Xu, Peng, primary, Chang, Jerry C., additional, Zhou, Xiaopu, additional, Wang, Wei, additional, Bamkole, Michael, additional, Wong, Eitan, additional, Bettayeb, Karima, additional, Jiang, Lu-Lin, additional, Huang, Timothy, additional, Luo, Wenjie, additional, Xu, Huaxi, additional, Nairn, Angus C., additional, Flajolet, Marc, additional, Ip, Nancy, additional, Li, Yue-Ming, additional, and Greengard, Paul, additional

Published
2020
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45. Association of SPI1 Haplotypes with Altered SPI1 Gene Expression and Alzheimer's Disease Risk.

Author

Cao, Han, Zhou, Xiaopu, Chen, Yu, Ip, Fanny C.F., Chen, Yuewen, Lai, Nicole C.H., Lo, Ronnie M.N., Tong, Estella P.S., Mok, Vincent C.T., Kwok, Timothy C.Y., Fu, Amy K.Y., Ip, Nancy Y., and Alzheimer’s Disease Neuroimaging Initiative

Subjects
*DISEASE risk factors, *GENE expression, *HAPLOTYPES, *SINGLE nucleotide polymorphisms, *CHINESE people, *ALZHEIMER'S disease, *GENETIC polymorphisms, *DISEASE susceptibility
Abstract

Background: Genetic studies reveal that single-nucleotide polymorphisms (SNPs) of SPI1 are associated with Alzheimer's disease (AD), while their effects in the Chinese population remain unclear.Objective: We aimed to examine the AD-association of SPI1 SNPs in the Chinese population and investigate the underlying mechanisms of these SNPs in modulating AD risk.Methods: We conducted a genetic analysis of three SPI1 SNPs (i.e., rs1057233, rs3740688, and rs78245530) in a Chinese cohort (n = 333 patients with AD, n = 721 normal controls). We also probed public European-descent AD cohorts and gene expression datasets to investigate the putative functions of those SNPs.Results: We showed that SPI1 SNP rs3740688 is significantly associated with AD in the Chinese population (odds ratio [OR] = 0.72 [0.58-0.89]) and identified AD-protective SPI1 haplotypes β (tagged by rs1057233 and rs3740688) and γ (tagged by rs3740688 and rs78245530). Specifically, haplotypes β and γ are associated with decreased SPI1 gene expression level in the blood and brain tissues, respectively. The regulatory roles of these haplotypes are potentially mediated by changes in miRNA binding and the epigenetic landscape. Our results suggest that the AD-protective SPI1 haplotypes regulate pathways involved in immune and neuronal functions.Conclusion: This study is the first to report a significant association of SPI1 with AD in the Chinese population. It also identifies SPI1 haplotypes that are associated with SPI1 gene expression and decreased AD risk. [ABSTRACT FROM AUTHOR]

Published
2022
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46. Genetic and polygenic risk score analysis for Alzheimer’s disease in the Chinese population

Author

Zhou, Xiaopu, Chen, Yu, Ip, Fanny Chui Fun, Lai, Nicole C.H., Li, Yuen Tung, Jiang, Yuanbing, Zhong, Huan, Chen, Yuewen, Zhang, Yulin, Ma, Shuangshuang, Lo, Ronie M.N., Cheung, Kit, Tong, Pui Sze, Ko, Ho, Shoai, Maryam, Mok, Kin Ying Boniface, Hardy, John, Mok, Vincent C.T., Kwok, Timothy C.Y., Fu, Kit Yu, Ip, Nancy Yuk-yu, Zhou, Xiaopu, Chen, Yu, Ip, Fanny Chui Fun, Lai, Nicole C.H., Li, Yuen Tung, Jiang, Yuanbing, Zhong, Huan, Chen, Yuewen, Zhang, Yulin, Ma, Shuangshuang, Lo, Ronie M.N., Cheung, Kit, Tong, Pui Sze, Ko, Ho, Shoai, Maryam, Mok, Kin Ying Boniface, Hardy, John, Mok, Vincent C.T., Kwok, Timothy C.Y., Fu, Kit Yu, and Ip, Nancy Yuk-yu

Abstract

Introduction: Dozens of Alzheimer's disease (AD)‐associated loci have been identified in European‐descent populations, but their effects have not been thoroughly investigated in the Hong Kong Chinese population. / Methods: TaqMan array genotyping was performed for known AD‐associated variants in a Hong Kong Chinese cohort. Regression analysis was conducted to study the associations of variants with AD‐associated traits and biomarkers. Lasso regression was applied to establish a polygenic risk score (PRS) model for AD risk prediction. / Results: SORL1 is associated with AD in the Hong Kong Chinese population. Meta‐analysis corroborates the AD‐protective effect of the SORL1 rs11218343 C allele. The PRS is developed and associated with AD risk, cognitive status, and AD‐related endophenotypes. TREM2 H157Y might influence the amyloid beta 42/40 ratio and levels of immune‐associated proteins in plasma. / Discussion: SORL1 is associated with AD in the Hong Kong Chinese population. The PRS model can predict AD risk and cognitive status in this population.

Published
2020

48. Large-scale plasma proteomic profiling identifies a high-performance biomarker panel for Alzheimer’s disease screening and staging.

Author

Yuanbing Jiang, Zhou, Xiaopu, Ip, Fanny C., Chan, Philip, Yu Chen, Lai, Nicole C. H., Cheung, Kit, Lo, Ronnie M. N., Tong, Estella P. S., Wong, Bonnie W. Y., Chan, Andrew L. T., Mok, Vincent C. T., Kwok, Timothy C. Y., Mok, Kin Y., Hardy, John, Zetterberg, Henrik, Fu, Amy K. Y., and Ip, Nancy Y.

Abstract

Introduction: Blood proteins are emerging as candidate biomarkers for Alzheimer’s disease (AD). We systematically profiled the plasma proteome to identify novel AD blood biomarkers and develop a high-performance, blood-based test for AD. Methods: We quantified 1160 plasma proteins in a Hong Kong Chinese cohort by high-throughput proximity extension assay and validated the results in an independent cohort. In subgroup analyses, plasma biomarkers for amyloid, tau, phosphorylated tau, and neurodegeneration were used as endophenotypes of AD. Results: We identified 429 proteins that were dysregulated in AD plasma. We selected 19 “hub proteins” representative of the AD plasma protein profile, which formed the basis of a scoring system that accurately classified clinical AD (area under the curve = 0.9690–0.9816) and associated endophenotypes. Moreover, specific hub proteins exhibit disease stage-dependent dysregulation, which can delineate AD stages. Discussion: This study comprehensively profiled the AD plasma proteome and serves as a foundation for a high-performance, blood-based test for clinical AD screening and staging. [ABSTRACT FROM AUTHOR]

Published
2022
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49. Genetic and polygenic risk score analysis for Alzheimer's disease in the Chinese population

Author

Zhou, Xiaopu, primary, Chen, Yu, additional, Ip, Fanny C. F., additional, Lai, Nicole C. H., additional, Li, Yolanda Y. T., additional, Jiang, Yuanbing, additional, Zhong, Huan, additional, Chen, Yuewen, additional, Zhang, Yulin, additional, Ma, Shuangshuang, additional, Lo, Ronnie M. N., additional, Cheung, Kit, additional, Tong, Estella P. S., additional, Ko, Ho, additional, Shoai, Maryam, additional, Mok, Kin Y., additional, Hardy, John, additional, Mok, Vincent C. T., additional, Kwok, Timothy C. Y., additional, Fu, Amy K. Y., additional, and Ip, Nancy Y., additional

Published
2020
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