Neurodegenerative diseases are an emerging global health crisis, with the projected global cost of dementia alone expected to exceed $1 trillion, or >1% of world GDP, by 2018. However, there are no disease-modifying treatments for the major neurodegenerative diseases, such as Alzheimer’s disease, Parkinson’s disease, frontotemporal lobar degeneration (FTLD), and amyotrophic lateral sclerosis. Therefore, there is an urgent need for a better understanding of the pathophysiology underlying these diseases. While genome-wide association studies (GWAS) have identified ~200 genetic variants that are associated with risk of developing neurodegenerative disease, the biological mechanisms underlying these associations are largely unknown. This dissertation investigates the mechanisms by which common genetic variation at TMEM106B, a GWAS-identified risk locus for FTLD, influences disease risk. First, using genetic and clinical data from thirty American and European medical centers, I demonstrate that the TMEM106B locus acts as a genetic modifier of a common Mendelian form of FTLD. Second, I investigate the role of increased TMEM106B expression levels, which have been reported both in FTLD patients and in individuals carrying the TMEM106B risk allele, in FTLD pathogenesis. I demonstrate that microRNA-132, the most dysregulated microRNA in a genome-wide screen of FTLD and control brains, directly represses TMEM106B expression in human cells, and likely contributes to the elevated TMEM106B levels seen in disease. I then combine statistical approaches, bioinformatics, and experimental approaches in order to functionally characterize all candidate GWAS causal variants at the TMEM106B locus. This approach identifies a noncoding variant, rs1990620, which affects CTCF-mediated long-range chromatin interactions between distal regulatory elements, as the likely causal variant responsible for altering TMEM106B expression levels and disease risk. These results provide a plausible mechanism by which TMEM106B genotype and expression levels influence FTLD risk and clinical progression, and provide a general framework for elucidating the biological mechanisms underlying a disease-associated risk locus. Such an approach will be necessary in order to translate the thousands of loci associated with disease risk by GWAS into mechanistic understanding and therapeutic advances.