Dr. Liang Ma is a Research Scientist in the Department of Psychiatry at Stanford University Schools of Medicine. He completed his Ph.D. degree in Human Genetics at the University of Chinese Academy of Sciences (2014). He completed postdoctoral research fellowships in genetics at Johns Hopkins University School of Medicine and UTHealth.

During his graduate program, he studied potential genomic variants that contribute to schizophrenia risk by evaluating the two largest Han GWAS (Ma et al. 2013 Mol Psychiatry), CREB1 signal pathway (Ma et al. 2014 J Psychiatr Res), and mitochondria component NDUFS7 (Ma et al. 2013 Psychiatr Genet). During his fellowship, he studied which schizophrenia-related genomic variations, open chromatin regions, and DNA methylation sites are interacting with each other to influencing gene expression and splicing (Ma et al. 2019 Mol Psychiatry) (Ma et al. 2020 Mol Psychiatry). He has pioneered the analysis of human polygenic diseases that dissect gene structure and link the expression features to disease risk.

His research interest focuses on identifying risk genomic variations, genes, and in particular, splicing transcripts for human polygenic diseases; and investigate how genomic variations affect gene transcriptions and further contribute to diseases’ risk. He specialized in genomics studies (genome-wide association study (GWAS), studies of RNA-seq, ChIP-seq and DNA methylation in combination with whole-genome sequencing (WGS)), and functional studies by employing molecular biology and cell biology approach. He established methods to discover risk splicing expression features and experimentally validate them. Using omics data and the methods he developed, he has identified a list of genes that potentially increase the risk of schizophrenia.

Education & Certifications

  • B.S., Shanxi Agricultural University, Animal Science (2007)
  • M.S., Northwest A&F University, Animal Genetics (2010)
  • Ph.D., University of Chinese Academy of Sciences, Human Genetics (2014)


Work Experience

  • Postdoctoral fellow 1, Lieber Institute for Brain Development, Johns Hopkins University School of Medicine Campus (7/1/2014 - 6/30/2017)


    855 N Wolfe St #300, Baltimore, MD 21205, USA

  • Postdoctoral fellow 2, School of Biomedical Informatics, University of Texas Health Science Center at Houston (7/1/2017 - 11/30/2017)


    7000 Fannin Street, Suite 600, Houston, TX 77030

  • Postdoctoral fellow 3, Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine (12/1/2017 - 1/30/2019)


    265 Campus Dr, MC 5454, 265 Campus Drive, Palo Alto, CA 94305, USA

  • Research Scientist, Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine (2/1/2019 - Present)


    265 Campus Dr, MC 5454, 265 Campus Drive, Palo Alto, CA 94305, USA


All Publications

  • Variations and expression features of CYP2D6 contribute to schizophrenia risk. Molecular psychiatry Ma, L., Shcherbina, A., Chetty, S. 2020


    Genome-wide association studies (GWAS) have successfully identified 145 loci implicated in schizophrenia (SCZ). However, the underlying mechanisms remain largely unknown. Here, we analyze 1497 RNA-seq data in combination with their genotype data and identify SNPs that are associated with expression throughout the genome by dissecting expression features to genes (eGene) and exon-exon junctions (eJunction). Then, we colocalize eGene and eJunction with SCZ GWAS using SMR and fine mapping. Multiple ChIP-seq data and DNA methylation data generated from brain were used for identifying the causal variants. Finally, we used a hypothesis-free (no SCZ risk loci considered) enrichment analysis to determine implicated pathways. We identified 171 genes and eight splicing junctions located within four genes (SNX19, ARL6IP4, APOPT1, and CYP2D6) that potentially contribute to SCZ susceptibility. Among the genes, CYP2D6 is significantly associated with SCZ SNPs in eGene and eJunction. In-depth examination of the CYP2D6 region revealed that a nonsynonymous single nucleotide variant rs16947 is strongly associated with a higher abundance of CYP2D6 exon 3 skipping junctions. While we found rs133377 and other functional SNPs in high linkage disequilibrium with rs16947 (r2 = 0.9539), histone acetylation analysis showed they are located within active transcription start sites. Furthermore, our data-driven enrichment analysis showed that CYP2D6 is significantly involved in drug metabolism of codeine, tamoxifen, and citalopram. Our study facilitates an understanding of the genetic architecture of SCZ and provides new drug targets.

    View details for DOI 10.1038/s41380-020-0675-y

    View details for PubMedID 32047265

  • Variations and expression features of CYP2D6 contribute to schizophrenia risk biorxiv Ma, L., Chetty, S. 2019

    View details for DOI 10.1101/659102

  • Translational bioinformatics in mental health: open access data sources and computational biomarker discovery. Briefings in bioinformatics Tenenbaum, J. D., Bhuvaneshwar, K., Gagliardi, J. P., Fultz Hollis, K., Jia, P., Ma, L., Nagarajan, R., Rakesh, G., Subbian, V., Visweswaran, S., Zhao, Z., Rozenblit, L. 2019; 20 (3): 842–56


    Mental illness is increasingly recognized as both a significant cost to society and a significant area of opportunity for biological breakthrough. As -omics and imaging technologies enable researchers to probe molecular and physiological underpinnings of multiple diseases, opportunities arise to explore the biological basis for behavioral health and disease. From individual investigators to large international consortia, researchers have generated rich data sets in the area of mental health, including genomic, transcriptomic, metabolomic, proteomic, clinical and imaging resources. General data repositories such as the Gene Expression Omnibus (GEO) and Database of Genotypes and Phenotypes (dbGaP) and mental health (MH)-specific initiatives, such as the Psychiatric Genomics Consortium, MH Research Network and PsychENCODE represent a wealth of information yet to be gleaned. At the same time, novel approaches to integrate and analyze data sets are enabling important discoveries in the area of mental and behavioral health. This review will discuss and catalog into an organizing framework the increasingly diverse set of MH data resources available, using schizophrenia as a focus area, and will describe novel and integrative approaches to molecular biomarker discovery that make use of mental health data.

    View details for DOI 10.1093/bib/bbx157

    View details for PubMedID 29186302

    View details for PubMedCentralID PMC6585382

  • Schizophrenia risk variants influence multiple classes of transcripts of sorting nexin 19 (SNX19). Molecular psychiatry Ma, L., Semick, S. A., Chen, Q., Li, C., Tao, R., Price, A. J., Shin, J. H., Jia, Y., Brandon, N. J., Cross, A. J., Hyde, T. M., Kleinman, J. E., Jaffe, A. E., Weinberger, D. R., Straub, R. E. 2019


    Genome-wide association studies (GWAS) have identified many genomic loci associated with risk for schizophrenia, but unambiguous identification of the relationship between disease-associated variants and specific genes, and in particular their effect on risk conferring transcripts, has proven difficult. To better understand the specific molecular mechanism(s) at the schizophrenia locus in 11q25, we undertook cis expression quantitative trait loci (cis-eQTL) mapping for this 2 megabase genomic region using postmortem human brain samples. To comprehensively assess the effects of genetic risk upon local expression, we evaluated multiple transcript features: genes, exons, and exon-exon junctions in multiple brain regions-dorsolateral prefrontal cortex (DLPFC), hippocampus, and caudate. Genetic risk variants strongly associated with expression of SNX19 transcript features that tag multiple rare classes of SNX19 transcripts, whereas they only weakly affected expression of an exon-exon junction that tags the majority of abundant transcripts. The most prominent class of SNX19 risk-associated transcripts is predicted to be overexpressed, defined by an exon-exon splice junction between exons 8 and 10 (junc8.10) and that is predicted to encode proteins that lack the characteristic nexin C terminal domain. Risk alleles were also associated with either increased or decreased expression of multiple additional classes of transcripts. With RACE, molecular cloning, and long read sequencing, we found a number of novel SNX19 transcripts that further define the set of potential etiological transcripts. We explored epigenetic regulation of SNX19 expression and found that DNA methylation at CpG sites near the primary transcription start site and within exon 2 partially mediate the effects of risk variants on risk-associated expression. ATAC sequencing revealed that some of the most strongly risk-associated SNPs are located within a region of open chromatin, suggesting a nearby regulatory element is involved. These findings indicate a potentially complex molecular etiology, in which risk alleles for schizophrenia generate epigenetic alterations and dysregulation of multiple classes of SNX19 transcripts.

    View details for DOI 10.1038/s41380-018-0293-0

    View details for PubMedID 30635639

  • Splicing QTL of human adipose-related traits. Scientific reports Ma, L., Jia, P., Zhao, Z. 2018; 8 (1): 318


    Recently, genome-wide association studies (GWAS) have identified 11 loci associated with adipose-related traits across different populations. However, their functional roles still remain largely unknown. In this study, we aimed to explore the splicing regulation of these GWAS signals in a tissue-specific fashion. For adipose-related GWAS signals, we selected six adipose-related tissues (adipose subcutaneous, artery tibial, blood, heart left ventricle, muscle-skeletal, and thyroid) with the sample size greater than 80 for splicing quantitative trait loci (QTL) analysis using GTEx released datasets. We integrated GWAS summary statistics of nine adipose-related traits (an average of 2.6 million SNPs per GWAS), and splicing QTLs from 6 GTEx tissues with an average of 337,900 splicing QTL SNPs, and 684,859 junctions. Our filtering process generated an average of 86,549 SNPs and 162,841 exon-exon links (junctions) for each tissue. A total of seven exon-exon junctions in four genes (AKTIP, DTNBP1, FTO and UBE2E1) were found to be significantly associated with four SNPs that showed genome-wide significance with body fat distribution (rs17817288, rs7206790, rs11710420 and rs2237199). These splicing events might contribute to the causal effect on the regulation of ectopic-fat, which warrants further experimental validation.

    View details for DOI 10.1038/s41598-017-18767-z

    View details for PubMedID 29321599

    View details for PubMedCentralID PMC5762880

  • Melatonin attenuates MPTP-induced neurotoxicity via preventing CDK5-mediated autophagy and SNCA/α-synuclein aggregation. Autophagy Su, L. Y., Li, H., Lv, L., Feng, Y. M., Li, G. D., Luo, R., Zhou, H. J., Lei, X. G., Ma, L., Li, J. L., Xu, L., Hu, X. T., Yao, Y. G. 2015; 11 (10): 1745–59


    Autophagy is involved in the pathogenesis of neurodegenerative diseases including Parkinson disease (PD). However, little is known about the regulation of autophagy in neurodegenerative process. In this study, we characterized aberrant activation of autophagy induced by neurotoxin 1-methyl-4-phenyl-1, 2, 3, 6-tetrahydropyridine (MPTP) and demonstrated that melatonin has a protective effect on neurotoxicity. We found an excessive activation of autophagy in monkey brain tissues and C6 cells, induced by MPTP, which is mediated by CDK5 (cyclin-dependent kinase 5). MPTP treatment significantly reduced total dendritic length and dendritic complexity of cultured primary cortical neurons and melatonin could reverse this effect. Decreased TH (tyrosine hydroxylase)-positive cells and dendrites of dopaminergic neurons in the substantia nigra pars compacta (SNc) were observed in MPTP-treated monkeys and mice. Along with decreased TH protein level, we observed an upregulation of CDK5 and enhanced autophagic activity in the striatum of mice with MPTP injection. These changes could be salvaged by melatonin treatment or knockdown of CDK5. Importantly, melatonin or knockdown of CDK5 reduced MPTP-induced SNCA/α-synuclein aggregation in mice, which is widely thought to trigger the pathogenesis of PD. Finally, melatonin or knockdown of CDK5 counteracted the PD phenotype in mice induced by MPTP. Our findings uncover a potent role of CDK5-mediated autophagy in the pathogenesis of PD, and suggest that control of autophagic pathways may provide an important clue for exploring potential target for novel therapeutics of PD.

    View details for DOI 10.1080/15548627.2015.1082020

    View details for PubMedID 26292069

    View details for PubMedCentralID PMC4824603

  • Molecular evolution in the CREB1 signal pathway and a rare haplotype in CREB1 with genetic predisposition to schizophrenia. Journal of psychiatric research Ma, L., Wu, D. D., Ma, S. L., Tan, L., Chen, X., Tang, N. L., Yao, Y. G. 2014; 57: 84–89


    CREB1 is a cAMP responsive transcriptional factor which plays a key role in neural development. CREB1 signal pathway (CSP) has been implicated repeatedly in studies of predisposition for schizophrenia. We speculated that CSP has undergone positive selection during evolution of modern human and some genes that have undergone natural selection in the past may predispose to schizophrenia (SCZ) in modern time. Positive selection and association analysis were employed to explore the molecular evolution of CSP and association with schizophrenia. Our results showed a pan-ethnic selection event on NRG1 and CREB1, as confirmed in all 14 ethnic populations studied, which also suggested a selection process occurred before the "Out of Africa" scenario. Analysis of 62 SNPs covering 6 CSP genes in 2019 Han Chinese (976 SCZ patients and 1043 healthy individuals) showed an association of two SNPs (rs4379857, P = 0.009, OR [95% CI]: 1.200 [1.379-1.046]; rs2238751, P = 0.023, OR [95% CI]: 1.253 [1.522-1.032]) with SCZ. However, none of these significances survived after multiple testing corrections. Nonetheless, we observed an association of a rare CREB1 haplotype CCGGC (Bonferroni corrected P = 1.74 × 10(-5)) with SCZ. Our study showed that there was substantial population heterogeneity in genetic predisposition to SCZ, and different genes in the CSP pathway may predispose to SCZ in different populations.

    View details for DOI 10.1016/j.jpsychires.2014.06.008

    View details for PubMedID 25043418

  • Evaluating risk loci for schizophrenia distilled from genome-wide association studies in Han Chinese from Central China. Molecular psychiatry Ma, L., Tang, J., Wang, D., Zhang, W., Liu, W., Wang, D., Liu, X. H., Gong, W., Yao, Y. G., Chen, X. 2013; 18 (6): 638–39

    View details for DOI 10.1038/mp.2012.63

    View details for PubMedID 22584866

  • No association between genetic polymorphisms of the NDUFS7 gene and schizophrenia in Han Chinese. Psychiatric genetics Ma, L., Zhang, W., Tang, J., Tan, L., Yao, Y. G., Chen, X. 2013; 23 (1): 29–32


    Accumulating evidence suggests that mitochondrial dysfunction contributes toward the pathogenesis of psychiatric diseases. NADH dehydrogenase Fe-S protein 7 (NDUFS7), a subunit of respiratory chain complex I, has been reported recently to be associated with bipolar disorder. To test whether this gene can confer a wide variety of psychiatric disorders, we carried out a case-control association analysis of three tagging single-nucleotide polymorphisms (rs2074896, rs2074897, and rs2074898) in the NDUFS7 gene by sequencing 330 Han Chinese patients with schizophrenia and 330 well-matched healthy controls. We found no significant difference in the frequency distributions of alleles, genotypes, and haplotypes between the cases and the controls, indicating no active role of this gene in schizophrenia.

    View details for DOI 10.1097/YPG.0b013e32835862c5

    View details for PubMedID 22935918

  • Polymorphisms identification and associations of KLF7 gene with cattle growth traits LIVESTOCK SCIENCE Ma, L., Qu, Y. J., Huai, Y. T., Li, Z. J., Wang, J., Lan, X. Y., Zhang, C. L., Wang, J. Q., Chen, H. 2011; 135 (1): 1–7

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