Yiyi Ma, MD, MS, PhD

  • Assistant Professor of Neurological Sciences (in Neurology and in the Gertrude H. Sergievsky Center)
Profile Headshot


I have particular research interest in the epigenetic mechanisms and their interactions with genetic variations in humans using the population based statistical and epidemiological methodologies. Under this general theme, I have built up my research experiences in (1) the epigenetics and genetics at Apolipoprotein E (APOE) locus, which is well-replicated to contribute the strongest genetic risk to the sporadic late-onset Alzheimer's disease (AD); (2) initiating the focused functional researches on the CpG-related SNP (CGS), one special type of single nucleotide polymorphism (SNP) which alters the sequence of the CpG dinucleotides; (3) the precision medicine to study the gene-by-gene and gene-by-environment interactions; and (4) the studies of novel molecular features such as RNA editings. During my mentored research career development, I have intimately worked with the three well-known large consortium of CHARGE (the Cohorts for Heart and Aging Research in Genomic Epidemiology), ADGC (the Alzheimer's Disease Genetics Consortium), and AMP-AD (the Accelerating Medicines Partnership for Alzheimer's Disease). In addition, I have built up experience in the analysis of multi-omic datasets, including genome-wide association study (GWAS) of array-based genotypes, whole exome sequencing, and whole genome sequencing, DNA methylome-wide association study (MWAS), transcriptome-wide association study (TWAS) of array-based transcriptomes and RNA sequencing platform, proteomics, metabolomics, dietary food frequency questionnaires.

At APOE locus, I have conducted researches to understand its epigenetic patterns, interaction with aging and diet, and genetic mechanisms related to AD and its risk factor of dyslipidemia. I was the first one to publish the landscape of the DNA methylation pattern at APOE in the human primary peripheral CD4+ T cells from approximately 1,000 European White subjects (Ma et al., Aging Cell, 2015). Based on methylation levels and the genetic regions, we categorized the 13 APOE CpG sites into three groups: Group 1 showed hyper-methylation (> 50%) and were located in the promoter region, Group 2 exhibited hypo-methylation (< 50%) and were located in the first two exons and introns, and Group 3 showed hyper-methylation (> 50%) and were located in the last exon 4, the exon harboring the two SNPs constituting different APOE ε isoforms. With the data from the Encyclopedia of DNA Elements (ENCODE) consortium, APOE methylation was negatively correlated with gene expression (minimum r = -0.66, P = 0.004) across different cell types. In addition, I have found that APOE methylation was significantly associated with age (minimum P = 2.06E-08) and plasma total cholesterol (minimum P = 3.53E-03). Finally, APOE methylation patterns differed across APOE ε variants (minimum P = 3.51E-05) and the promoter variant rs405509 (minimum P = 0.01), which further showed a significant interaction with age (P = 0.03). Our discovery of the DNA methylation patterns at APOE and its differences by APOE ε variants are recently replicated by an independent UK group. Later, I have conducted a meta-analysis across seven independent cohorts from the CHARGE consortium and found a possible interaction between an APOE promoter SNP and the circulating level of the α-linoleic acid (ALA), one of the essential N3 polyunsaturated fatty acids (N3-PUFAs) to modulate the blood levels of APOE DNA methylation (Ma et al., American Journal of Clinical Nutrition, 2016). With the support from the ADGC consortium, I have published an APOE ε4-stratified genome-wide association study (GWAS) based on the whole exome sequencing data to explore the candidate genetic loci masked by the APOE ε4. I have replicated the previous reported MAPT locus and identified novel loci at GPAA1 which was functionally validated by the support of AMP-AD whole-genome sequencing and RNA sequencing datasets (Ma et al., JAMA Neurology, 2019). Recently, by conducting the brain DNA methylome-wide association study (MWAS), I have identified a brain epigenetic feature which have the potential to reduce the risk effect of APOE ε4 on AD. I further conducted a transcriptome-wide association study (TWAS) and found that this epigenetic feature regulated the transcription program of microglia. Our findings are also replicated in the other four smaller collections of brain data. These findings are selected as an oral presentation for the Alzheimer's Association International Conference 2020 Virtual meeting and under review by the Alzheimer's & Dementia.

I was the first one to focus on the functional researches on the CpG-related SNPs (CGS), a special type of SNPs which can alter the sequence of CpG dinucleotides. In primary human tissues, the majority (90%) of DNA methylation occur on the CpG dinucleotides where the Cytosine is methylated. Across the human genome, there are approximately 25% SNPs annotated to be the CGS. On a genome-wide scale, I found that the DNA methylation patterns are associated with haplotypes of multiple CGSs within the same linkage disequilibrium (LD) block (P < 0.0001) (Ma et al., Genome-Wide Association Studies, chapter 13, Cambridge University Press, 2016). More interestingly, the two CGSs in high LD tend to carry the same type of alleles, either create or disrupt a CpG dinucleotides (P<0.0001). My initial findings were selected as an oral presentation on the 2013 annual meeting of the American Society of Human Genetics (ASHG) and later I was invited to write a book chapter and speak on the Meetings of Epigenomics & Metabolomics in Boston. During my first postdoctoral training at Boston University with the support from the ADGC, I was able to publish a genome-wide sliding window based approach to explore in a systematic way of the link between CGSs and AD. I have found that the AD related genetic windows of CGSs are enriched in the immune-related genes, i.e. <em>APOE, MS4A cluster, TREM2, BIN1, CR1, and PICALM. In addition, there is a dose-response relationship between the number of CpG dinucleotides from the included CGSs and the risk of AD (Ma et al., Aging Cell, 2019).

I also have experiences in the researches of precision medicine to study the gene-by-gene and gene-by-environment interactions related to AD, dyslipidemia and inflammation in both Whites and Hispanics. Besides the above described findings of the interactions at APOE locus, I also published my findings of the interactions at the lipoprotein lipase (LPL), ATP-binding cassette subfamily A member 1 (ABCA1), and interleukin 6 (IL6). I have found that the LPL genetic variant interacted with dietary intake of polyunsaturated fatty acids (PUFAs) to modulate the risk to obesity in Hispanic population (Ma et al., Nutr. Metab. Cardiovasc. Dis., 2014). I also found that the promoter SNP at ABCA1 interacted with circulating levels of eicosapentaenoic acid (EPA) to modulate the blood level of high density lipoprotein (HDL) and the DNA methylation levels at ABCA1. However, with the mediation analysis, we obtained little evidence that the observed ABCA1-by-EPA interactions on blood HDL act through DNA methylation changes in ABCA1 (Ma et al., American Journal of Clinical Nutrition, 2016). In the perspective of inflammation, I found that the DNA methylation level of IL6 was correlated with its mRNA expressions across different cell types and plasma concentrations of IL6 protein. In addition, higher circulating total n-3 PUFA was associated with lower IL6 methylation (P = 0.007) and lower IL6 plasma protein concentration (P = 0.02), and this association is dependent on the genotypes of a promoter SNP at IL6. (Ma et al., Mol. Nutr. Food Res., 2016).

Along with the genetics and epigenetics, I also have conducted one study to explore the biology of RNA editing, a molecular process that introduces another layer of variation in RNA. I have conducted the largest genome-wide human brain study to date, creating a resource which identifies RNA editing events in 1,865 samples across 9 brain regions from 1,074 subjects. Based on our unique data which include multiple brain regions and proteomes from the same subjects, we are able to study the mapping of RNA editing across different brain regions as well as the extent to which coding events affect the proteome. We expand the list of known brain editing events by identifying 58,761 previously unreported events. We note that only a small proportion of these editing events are found at the protein level in our proteome-wide validation effort. We also identified the occurrence of editing events associated with AD dementia, neuropathological measures and longitudinal cognitive decline in: SYT11, MCUR1, SOD2, ORAI2, HSDL2, PFKP, and GPRC5B. Thus, we present an extended reference set of brain RNA editing events, identify a subset that are found to be expressed at the protein level, and extend the narrative of transcriptomic perturbation in AD to RNA editing. The manuscript is currently under review by Nature Communication.

During my mentored trainings at doctoral and postdoctoral stages, I have intimately worked with the three well-known large consortium of CHARGE (the Cohorts for Heart and Aging Research in Genomic Epidemiology), ADGC (the Alzheimer's Disease Genetics Consortium), and AMP-AD (the Accelerating Medicines Partnership for Alzheimer's Disease). I am very familiar with the nature of datasets from each consortium by not only working on the analysis-read datasets but also conducting the quality control (QC) and data processing work. I was one of the two main persons who did the QC for the whole exome sequencing data of Alzheimer's Disease Sequencing Project (ADSP) and facilitated the workflow and generated the analysis-ready dataset released to the public. I was also in charge of the QC and data normalization of the monocyte RNA sequencing data for AMP-AD consortium. In addition, I have built up and maintained a wide collaboration networks across these large consortiums.

My long-term research career goal is to develop a clinical drug to treat AD. I do not believe there exists a "one-size-fit-all" drug especially for a complex disease as AD. My research experience not only has trained me in different modalities of the human biology and made me ready for the future challenges, but also has led me to the future research interest in developing a candidate AD drug based on APOE-relevant mechanism. In the near future, I am planning to start with the application of a K grant to get the peripheral proxies of the brain epigenetic feature I have found to reduce the risk effect of APOE ε4 on AD by embarking on the new adventure into the brain imaging field, which is much more accessible and clinically meaningful than the postmortem brain tissues. Although the long-term goal is very challenging, I believe I will contribute important evidence to the neurodegenerative diseases.

Academic Appointments

  • Assistant Professor of Neurological Sciences (in Neurology and in the Gertrude H. Sergievsky Center)


  • Female

Credentials & Experience

Education & Training

  • MD, 2005 Preventive Medicine, Fudan University, Shanghai, China
  • MS, 2008 Medicine Nutrition & Food Hygiene, Fudan University, Shanghai, China

Honors & Awards

  • 2001-2003 People’s Scholarship, Third Prize Fudan University Prize
  • 2003-2004 People’s Scholarship, Second Prize Fudan University Prize
  • 2006-2007 People’s Scholarship, Third Prize Fudan University Prize
  • 2008-2010 Provost Fellow, Gerald J. and Dorothy R. Friedman School of Nutrition Science and Policy at Tufts University Tufts University Prize
  • 2008-2014 Fellowship Gerald J. and Dorothy R. Friedman School of Nutrition Science and Policy at Tufts University Tufts University M.S. and Ph.D. Research Fellowship
  • 2019-2022 Systematic cataloging APOE ε4-stratified biology of Alzheimer's disease Alzheimer’s Association - Research Fellowship 2019-AARD-644521 PI: Yiyi Ma, M.D. Ph.D. Mentor: Philip L. De Jager, M.D. Ph.D. The goal of the fellowship is to extend the studies of the 22 single nucleotide polymorphisms (SNPs) identified to be associated with the risk of AD dementia stratified by APOE ε4 genotypes using the whole-exome sequencing data from the Alzheimer's disease sequencing project (ADSP).


Selected Publications

All manuscripts below are peer-reviewed and are "Research Investigations"

1. Ma Y, Guo H. Mini-review of studies on the carcinogenicity of deoxynivalenol. Environ. Toxicol. Pharmacol. 2008 Jan. PubMed PMID: 21783829.

2. Zheng JS, Arnett DK, Parnell LD, Lee YC, Ma Y, Smith CE, Richardson K, Li D, Borecki IB, Ordovas JM, Tucker KL, Lai CQ, “Genetic Variants at PSMD3 Interact with Dietary Fat and Carbohydrate to Modulate Insulin Resistance,” J. Nutr. 2013 Jan. PubMed PMID: 23303871 PMCID: PMC3713024

3. Zheng JS, Arnett DK, Parnell LD, Lee YC, Ma Y, Smith CE, Richardson K, Li D, Borecki IB, Ordovas JM, Tucker KL, Lai CQ, “Polyunsaturated fatty acids modulate the association between PIK3CA-KCNMB3 genetic variants and insulin resistance,” Plos One, 2013 Jun. PubMed PMID: 23826284 PMCID: PMC3694924

4. Ma Y, Tucker KL, Smith CE, Lee YC, Huang T, Richardson K, Parnell LD, Lai CQ, Young KL, Justice AE, Shao Y, North KE, Ordovas JM, “Lipoprotein lipase variants interact with polyunsaturated fatty acids for obesity traits in women: replication in two populations,” Nutrition, Metabolism & Cardiovascular Disease., 2014, Jul. PubMed PMID: 25156894 PMCID: PMC4356006

5. Parnell LD, Blokker BA, Dashti HS, Nesbeth PD, Cooper BE, Ma Y, Lee YC, Hou R, Lai CQ, Richardson K, Ordovas JM, “CardioG×E, a catalog of gene-environment interactions for cardiometabolic traits,” BioData Mining, 2014 Oct. PubMed PMID: 25368670 PMCID: PMC4217104

6. Zheng JS, Parnell LD, Smith CE, Lee YC, Jamal-Allial A, Ma Y, Li D, Tucker KL, Ordovas JM, Lai CQ, “Circulating 25-hydroxyvitamin D, IRS1 variant rs2943641, and insulin resistance: replication of a gene-nutrient interaction in 4 populations of different ancestries,” Clin. Chem., 2014 Jan.60(1):186-196. PubMed PMID: 24255076 PMCID: PMC4026060

7. Ma Y, Smith CE, Lai CQ, Irvin MR, Parnell LD, Lee YC, Pham L, Aslibekyan S, Claas SA, Tsai M, Borecki IB, Kabagambe EK, Berciano S, Ordovas JM, Absher D, Arnett DK, “Genetic variants modulate the effect of age on APOE methylation in the Genetics of Lipid Lowering Drugs and Diet Network study,” Aging Cell, 2015 Feb. PubMed PMID: 25476875 PMCID: PMC4324456

8. Ma Y, Smith CE, Lai CQ, Irvin MR, Parnell LD, Lee YC, Pham L, Aslibekyan S, Claas SA, Tsai M, Borecki IB, Kabagambe EK, Ordovas JM, Absher D, Arnett DK, “The effects of omega-3 polyunsaturated fatty acids and genetic variants on methylation levels of the interleukin-6 gene promoter,” Mol. Nutr. Food Res. 2015.Oct. PubMed PMID: 26518637 PMCID: PMC4844557

9. Smith CE, Follis JL, Nettleton JA, Foy M, Wu JHY, Ma Y, et al., “Dietary fatty acids modulate associations between genetic variants and circulating fatty acids in plasma and erythrocyte membranes: Meta-analysis of nine studies in the CHARGE consortium,” 2014. Molecular Nutrition and Food Research. 2015 Jan. PubMed PMID: 25626431 PMCID: PMC4491005.

10. Zhang S, Ma Y, Guo H, Wan W, Xue K, “Diets high in carbohydrate may not be appropriate for rs328 G carriers with the metabolic syndrome,” Asia Pac. J. Clin. Nutr. 2015;24(3):546-554. PubMed PMID: 26420199.

11. Ma Y, Follis JL, Smith CE, Tanaka T, Manichaikul AW, Chu AY, Samieri C, Zhou X, Guan W, Wang L, Biggs ML, Chen YD, Hernandez DG, Borecki I, Chasman DI, Rich SS, Ferrucci L, Irvin MR, Aslibekyan S, Zhi D, Tiwari HK, Claas SA, Sha J, Kabagambe EK, Lai CQ, Parnell LD, Lee YC, Amouyel P, Lambert JC, Psaty BM, King IB, Mozaffarian D, McKnight B, Bandinelli S, Tsai MY, Ridker PM, Ding J, Mstat KL, Liu Y, Sotoodehnia N, Barberger-Gateau P, Steffen LM, Siscovick DS, Absher D, Arnett DK, Ordovás JM, Lemaitre RN, “Interaction of methylation-related genetic variants with circulating fatty acids on plasma lipids: a meta-analysis of 7 studies and methylation analysis of 3 studies in the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium,” Am J Clin Nutr. 2016 Feb;103(2):567-78. PubMed PMID: 26791180 PMCID: PMC5260796

12. Ma Y, Ordovas JM. "The integration of epigenetics and genetics in nutrition research for CVD risk factors". Proc. Nutr. Soc., 2017 Aug; 76(3):333-346. PubMed PMID: 27919301

13. Blue EE, Bis JC, Dorschner MO, Tsuang DW, Barral SW, Beecham G, Below JE, Bush WS, Butkiewicz M, Cruchaga C, Destefano A, Farrer LA, Goat A, Haines J, Jaworski J, Jun G, Kunkle B, Kuzma A, Lee JJ, Lunetta KL, Ma Y, Martin E, Naj A, Nato AQ, Navas P, Nguyen H, Reitz C, Reyes D, Salerno W, Schellenberg GD, Seshadri S, Sohi H, Thornton TA, Valadares W, van Duijn C, Vardarajan BN, Wang LS, Boerwinkle E, Dupuis J, Pericak-Vance MA, Mayeux R, Wijsman EM; on behalf of the Alzheimer's Disease Sequencing Project, “Genetic variation in genes underlying diverse dementias may explain a small proportion of cases in the Alzheimer’s Disease Sequencing Project”. Dement. Geriatr. Cogn. Disord. 2018;45(1-2):1-17. PubMed PMID: 29486463.

14. Bis JC, Jian X, Kunkle BW, Chen Y, Hamilton-Nelson KL, Bush WS, Salerno WJ, Lancour D, Ma Y, Renton AE, Marcora E, Farrell JJ, Zhao Y, Qu L, Ahmad S, Amin N, Amouyel P, Beecham GW, Below JE, Campion D, Cantewell L, Charbonnier C, Chung J, Crane PK, Cruchaga C, Cupples LA, Cartigues JF, DEbette S, Deleuze JF, Fulton L, Gabriel SB, Genin E, Gibbs RA, Goate A, Grenier-Boley B,, Gupta N, Haines JL, Havulinna AS, Helisalmi S, Hiltunen M, Howrigan DP, Ikram MA, Kaprio J, Konrad J, Kuzma A, Lander ES, Lathroop M, Lehtimaki T, Lin H, Mattila K, Mayeux R, Muzny DM, Nasser W, Neale B, Nho K, Nicolas G, Patel D, Pericak-Vance MA, Perola M, Psaty BM, Quenez O, Rajabli F, Rendon R, Reitz C, Remes AM, Salomaa V, Sarnowski C, Schmidt H, Schmidt M, Schmidt R, Soininen H, Thornton TA, Tosto G, Tzourio C, van der Lee SJ, van Duijn CM, Valladares O, Vardarajan B, Wang LS, Wang W, Wijsman E, Wilson RK, Witten D, Worley KC, Zhang X; Alzheimer's Disease Sequencing Project, Bellenguez C, Lambert JC, Kurki MI, Palotie A, Daly M, Boerwinkle E, Lunetta KL, Destefano AL, Dupuis J, Martin ER, Schellenberg GD, Seshadri S, Naj AC, Fornage M, Farrer LA, “Whole exome sequencing study identifies novel rare and common Alzheimer’s-associated variants involved in immune response and transcriptional regulation”. Mol. Psychiatry. 2018 Aug 14. Doi:10.1038/s41380-018-0112-7. PubMed PMID: 30108311.

15. Ma Y, De Jager PL. “Designing an epigenomic study”. Mult. Scler. 2018 Apr;24(5):604-609. PubMed PMID: 29692225.

16. Chung J, Zhang X, Allen M, Wang X, Ma Y, et al., “Genome-wide pleiotropy analysis of neuropathological traits related to Alzheimer’s disease”. Alzheimers Res. Ther., 2018 Feb. 20;10(1):22. Doi: 10.1186/s13195-018-0349-z. PubMed PMID: 29458411.

17. Chung J, Wang X, Maruyama T, Ma Y, Kim M, Zhang X, Mez J, Sherva R, Takeyama H, The Alzheimer’s Disease Neuroimaging Initiative, K.L. Lunetta, L.A. Farrer, and G.R. Jun, “Genome-wide association study of Alzheimer’s disease endophenotypes at preclinical and MCI stages”, Alzheimers Dement. 2018 May;14(5):623-633, PubMed PMID: 29274321.

18. De Jager PL, Ma Y, McCabe C, Xu J, Vardarajan BN, Felsky D, Klein HU, White CC, Peters MA, Lodgson B, Nejad P, Tang A, Mangravite LM, Yu L, Gaiteri C, Mostafavi S, Schneider JA, Bennett DA. “A multi-omic atlas of the human frontal cortex for aging and Alzheimer’s disease research”. Sci. Data., 2018 Aug. 7;5:180142. PubMed PMID: 30084846.

19. Ng B, Casazza W, Patrick E, Tasaki S, Novakovsky G, Felsky D, Ma Y, Bennett DA, Gaiteri C, De Jager PL, Mostafavi S. “Using transcriptomic hidden variables to infer context-specific genotype effects in the brain”. Am. J. Hum. Genet., 2019 Sep. 5; 105(3):562-572. PubMed PMID: 31447098

20. Naj AC, Vardarajan BN, White W, Lancour D, Ma Y, et al., “Quality control and integration of genotypes from two calling pipelines for whole genome sequence data in the Alzheimer’s disease sequencing project”. Genomics. 2019 Jul;111(4):808-818. PubMed PMID: 29857119.

21. Ma Y, Jun GR, Zhang X, Chung J, Naj AC, Bellenguez C, Hamilton-Nelson K, Martin ER, Kunkle BW, Bis JC, Debette S, DeStefano AL, Fornage M, Nicolas G, van Duijn C, Bennett DA, De Jager PL, Mayeux R, Haines JL, Pericak-Vance MA, Seshadri S, Lambert JC, Schellenberg GC, Lunetta KL, Farrer LA, Alzheimer’s Disease Sequencing Project and Alzheimer’s Disease Exome Sequencing-France Project “Analysis of whole-exome sequencing data for Alzheimer Disease stratified by APOE genotype” JAMA Neurol. 2019 Jun 10. Doi:10.1001/jamaneurol.2019.1456. PubMed PMID: 31180460

22. Ma Y, Jun GR, Chung J, Zhang X, Kunkle BW, Naj AC, White CC, Bennett DA, De Jager PL, ADGC, Mayeux R, Haines JL, Pericak-Vance MA, Schellenberg GD, Farrer LA, Lunetta KL, “CpG-related SNPs in the MS4A region have a dose-response effect on risk of late-onset Alzheimer disease” Aging Cell. 2019 Aug:18(4)e12964. PubMed PMID: 27919301

23. Zhang X, Zhu C, Beecham G, Vardarajan BN, Ma Y, Lancour D, Farrell JJ, Chung J; Alzheimer’s Disease Sequencing Project, Mayeux R, Haines JL, Schellenberg GD, Pericak-Vance MA, Lunetta KL, Farrer LA. “A rare missense variant of CASP7 is associated with familiar late-onset Alzheimer’s disease”. Alzheimers Dememt., 2019 Mar; 15(3):441-452. PubMed PMID: 30503768

24. Ng B, Casazza W, Patrick E, Tasaki S, Novakovsky G, Felsky D, Ma Y, Bennett DA, Gaiteri C, De Jager PL, Mostafavi S. "Using transcriptomic hidden variables to infer context-specific genotype effects in the brain." Am. J. Hum. Genet., 2019 Sep.; 105(3):562-572. PubMed PMID: 31447098

25. Yang HS, White CC, Klein HU, Yu L, Gaiteri C, Ma Y, Felsky D, Mostafavi S, Petyuk VA, Sperling RA, Ertekin-Taner N, Schneider JA, Bennett DA, De Jager PL. "Genetics of gene expression in the aging human brain reveal TDP-43 proteinopathy pathophysiology". Neuron, 2020 Jun.; accepted.

26. De Jager C, White CC, Bennett D, Ma Y. "Neuroticism alters the transcriptiome of the frontal cortex to contribute to the cognitive decline and onset of Alzheimer's disease". Translational Psychiatry, 2020 Dec., Accepted.

Book chapter: Non-peer reviewed scientific or medical publications/materials in print or other media

1. Lai CQ, Ma Y, Parnell LD. Genetics and gene-environment interactions on longevity and lifespan.Book: Gene-environment interactions and human diseases, Chapter 12.,2015

2. Ma Y, Smith CE, Lee YC, Parnell LD, Lai CQ, Ordovas JM. Haplotypes of CpG-related SNPs and associations with DNA methylation patterns. Book: Genome-Wide Association Studies: From Polymorphism to Personalized Medicine, Chapter 13., 2016.