PhD Application Insights on Vascular Contributions to SVD and AD

These flashcards cover key insights and concepts from a lecture regarding a PhD application focusing on vascular contributions to small vessel disease (SVD) and Alzheimer's disease (AD), including methods, challenges, and desired skills.

What are the vascular contributors to SVD and AD seen as in research?

Often treated as confounders rather than modifiers.

What does multi-omic integration encompass in the context of this PhD?

Genetics, epigenetics, imaging, RNA-seq, proteomics, and blood biomarkers.

How does epigenetics differ from genetics in relation to disease?

Genetics is static, while epigenetics is dynamic and context-dependent.

What is a significant feature of GWAS variants according to the notes?

Many GWAS variants are non-coding and act through regulatory mechanisms.

What is the relationship between Alzheimer’s disease and SVD?

They are biologically related but mechanistically distinct diseases.

What role does APOE play in Alzheimer’s disease?

It is a major AD risk factor but not consistently linked to WMHs.

What prepares a candidate's pharmacology background for a PhD in this area?

Training in molecular mechanisms of monogenic and polygenic diseases.

How does epigenetics enhance the understanding of causation in GWAS studies?

It provides biological context like cell type, timing, and state.

What is the purpose of Mendelian randomization?

It uses genetic variants as instrumental variables to test causality.

What is one limitation of epigenetic studies mentioned in the notes?

Difficult to disentangle cause vs consequence.

What characterizes a good biomarker for vascular dementia?

Disease-relevant, detectable early, and ideally non-invasive.

Why is blood-based data considered useful for a brain disease?

It captures systemic processes and reflects upstream drivers of brain vulnerability.

How should one approach negative results in research?

View them as informative, not failures; reassess and refine models.

What is a key method for handling uncertainty in research?

Triangulate evidence across methods and state assumptions clearly.

What skills does the applicant want to develop during their PhD?

Causal inference, independent hypothesis testing, and translating complex data.

What does success look like after completing the PhD?

Robust findings and clear mechanistic understanding.