A veteran of the Neurology Department with 15 years at Duke, Michael Lutz, PhD, Associate Professor in the Translational Brain Sciences Division, recently reached his 100th peer-reviewed publication. In 2016, Dr. Lutz was the subject of one of our first Faculty Spotlight Interviews. We caught up with him again to talk about some of the advancements in his research over the past 8 years, as well as his new and changing roles in the Department.
What are your responsibilities within the Neurology Department?
My responsibilities within the Department span projects that involve clinical, translational, and basic research. Many of these are grant-funded projects for Alzheimer’s disease or other neurodegenerative disease research that have substantial genetics, computational biology, or biostatistics components.
The focus of my work is to more clearly understand the genetic and biological mechanisms involved in these diseases. Therefore, my studies include clinical trials, animal model work, and biochemistry/molecular genetics. Identification and characterization of biomarkers for disease is also an important focus.
I co-lead the Data Management and Statistics Core of the Duke/UNC Alzheimer’s Disease Research Center (ADRC). In that role, I am working with a team of data scientists, database managers, and statisticians to develop the database infrastructure for the ADRC, and to provide bioinformatics and biostatistical support for projects at Duke and UNC that are focused on Alzheimer’s disease research. Finally, I provide statistical analysis support for faculty and students in the Neurology department.
What does your typical day look like?
One aspect of my job that I like is that there isn’t a typical day! I spend a good part of each day analyzing data: clinical data, data from laboratory experiments and public domain datasets (e.g. large genetic, genomic, proteomic, metabolomic datasets). Another part of each day involves writing grants and publications. Collaboration, consulting and teaching are other activities that round out my day.
Since my last interview in 2016, the statistical consulting aspect of my “typical day” has definitely increased! I am now working on projects across the Neurology divisions that range from discussion of ideas for grants to projects that result in multiple publications. I work with collaborators at Duke and around the world on projects that involve Alzheimer’s disease, neurodegenerative diseases, and age-related diseases. I work with collaborators and students to design studies and analyze data from a genetics and bioinformatics perspective. An important part of my day involves working with collaborators in the Neurology Department on projects that involve statistical analysis.
You recently co-authored an article in Alzheimer’s & Dementia discussing a “bioinformatics pipeline” of short structural variants relating to late-onset Alzheimer’s disease. What were the main findings of that article, and how will they help future research?
This is collaborative work with Dr. Ornit Chiba-Falek. Many, if not most, human genetic studies examine genetic variation at the level of single nucleotide polymorphisms or SNPs. However, there are other types of genetic variation that are understudied: structural variants including deletions, insertions, and repeating sequences.
This paper provided an analytical framework to catalog and prioritize short structural variants (SSVs) in candidate cis-regulatory elements (cCREs) located in Alzheimer’s disease genome-wide association study (GWAS) loci and characterize their putative effects on transcription factor (TF) binding sites.
This study extended prior work with cCREs within Alzheimer’s disease GWAS regions to include SSVs and to rank the top candidate SSV/TF pairs for validation experiments. The bioinformatics pipeline was utilized to characterize several Alzheimer’s GWAS loci, including SPI1 and APOE. This sets the stage to study the effect of the different SSV variants using gene editing techniques such as clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated (Cas) technologies.
Future studies would focus on generating isogenic human induced pluripotent stem cells (hiPSC) lines for the candidate SSVs identified by our bioinformatics pipeline and evaluate their cis-regulatory effects in the respective brain cell type by differentiation into microglia, astrocytes, and neurons. These studies would confirm the effect of the SSV on gene transcription, the linked target gene, and the TF that mediate the effect. Follow-up analyses could use three-dimensional (3D) models, including organoids and co-cultures, to further examine impact on downstream cellular mechanisms, neurodegeneration, and other disease perturbations. This knowledge would be essential for the development of new therapeutic targets for the prevention and treatment of Alzheimer’s disease.
What other research projects are you involved with at the moment?
The diversity of my research project portfolio is another aspect of my job that I enjoy. These projects are highly collaborative and allow me to work with investigators in our department, across Duke, and internationally. I am working with Drs. Carol Colton, Kirby Gottschalk, and other faculty on a project to understand how biological sex and APOE genotype interact to alter immune regulated metabolism in AD.
I am collaborating with Drs. Rich O’Brien, Gabriel Torrealba-Acosta, and investigators at Johns Hopkins on an extensive analysis of CSF and serum proteomics to “untangle” the effects of age, sex, and APOE genotype on the proteome of individuals with MCI and AD. We are using statistical models of mediation as one tool for this project. I am working with Drs. Miles Berger, Sheng Luo, and Haotian Zou on a different proteomics project to investigate APOE4 dependent regulation of CSF Complement Pathway Activation in the development of Alzheimer's disease. With Dr. Ornit Chiba-Falek and members of her lab, I am working on a project to understand Lewy body neuropathologies and the genetics of SNCA gene: variants expression and splicing (this work is relevant to Parkinson’s disease).
With Dr. Sheng Luo, I am working on integrative modeling and dynamic prediction of Alzheimer's disease using novel statistical methods. I am collaborating with Dr. Alexandra Badea in the Department of Radiology to examine brain networks in mouse models of aging. This work has led to the development of some new statistical models that have more general applicability to problems that involve the combination of imaging data and transcriptomic data. I am working with Dr. Don Sanders on approaches to utilize over 40 years of data from the Duke myasthenia gravis registry to analyze outcome measures that have potential utility for clinical trials.
Your first Spotlight interview with the Neurology Department was in 2016. What would you say is the biggest or most interesting advance in our understanding of neurodegenerative disease that we’ve had since then?
One advance worth highlighting is single-cell RNA-seq (scRNA-seq) as a platform for neurodegenerative disease research. This technology allows research programs to investigate transcriptomic changes at unprecedented spatial and molecular levels: inhibitory neurons, excitatory neurons, microglia. Data from scRNA-seq experiments allows us to better understand the mechanisms that drive neurodegenerative diseases and how they are similar or different between the different diseases. Neurodegenerative diseases such as Alzheimer’s disease, Parkinson’s disease, and amyotrophic lateral sclerosis have been molecularly subtyped, dysregulated pathways have been identified, and potential therapeutic targets have been revealed using scRNA-seq. Studies using these data have allowed investigation of the role that dysregulation of the immune system plays in neurodegenerative diseases.
What pending advances in our understanding of the genetics of Alzheimer’s disease (or just translational neuroscience in general) are you most excited about?
There are advances in multiple aspects of translational neuroscience that I am excited about. It is a very exciting time to be working in the field since so many laboratory and computational tools have advanced to levels that we would have not even dreamed about decades ago.
On the laboratory side gene editing allows testing of hypotheses that result from computational studies, simulation, and mining of large public databases. On the computational side, in addition to advances in computational power, the availability of large-scale cohort studies, and biobanks. DNA sequencing, brain scans, cognitive tests, and other types of data present the opportunity to test ideas thoroughly by integration and analysis of these diverse data types.
New algorithms based on machine learning and new statistical methodology for longitudinal studies allow investigators to ask questions of the data with respect to specific hypotheses around biological mechanisms and to identify potential targets for therapies.
What do you enjoy most about your work?
I like the intellectual engagement of my work. Science involves clear definition of impactful projects to pursue, and at the same time development of innovative ways to apply the various tools (laboratory, clinical trials, computational models) that we have available to these projects. My work is centered on both of these aspects of research: defining the questions in order to develop grant proposals that have impact, and working on the approaches to analyze the vast data that is available in the public domain and that is acquired for specific projects.
What’s the hardest part of your job?
Recognition that there are far more good ideas to investigate than I would ever have time to study in depth. As I work on different projects, read scientific papers, and attend conferences, I usually have a large number of ideas that I want to investigate. Sometimes, it is an algorithm or software package, but just as often it is a major concept or idea. To pursue many of these requires writing a grant to fund the work, or finding some way to at least test proof of concept which takes a substantial amount of time. So, I have to prioritize and try to decide the best way forward for many competing priorities.
What passions or hobbies do you have outside of Duke?
It is hard to identify passions that are outside of the department, because the biggest one, science, spans both my Duke and “outside of Duke” life. I enjoy reading about science and speaking with people about it. Interestingly, a passion that has been unchanged from high school is using math and computers for problems in biology. Sharing my approaches to solve problems is a passion, as is teaching and writing.
Hobbies are many, but finding the time for them is challenging. I enjoying running and I try to get out 4-6 times each week for a run on the great trails that we have in the area. During the summer, I enjoy going to the lake for a long swim. I enjoy gardening, hiking, and working on projects around the house. Most recently, I have been working on nature photography skills, especially before a trip to Costa Rica. The pictures below were from that trip.
