Frontotemporal lobar degeneration with TDP-43 inclusions (FTLD-TDP) is a fatal neurodegenerative disease with no available treatments. Mutations in the progranulin gene (GRN) causing impaired production or secretion of progranulin are a common Mendelian cause of FTLD-TDP; additionally, common variants at chromosome 7p21 in the uncharacterized gene TMEM106B were recently linked by genome-wide association to FTLD-TDP with and without GRN mutations. Here we show that TMEM106B is neuronally expressed in postmortem human brain tissue, and that expression levels are increased in FTLD-TDP brain. Furthermore, using an unbiased, microarray-based screen of over 800 microRNAs, we identify microRNA-132 as the top microRNA differentiating FTLD-TDP and control brains, with <50% normal expression levels of three members of the microRNA-132 cluster (microRNA-132, microRNA-132*, and microRNA-212) in disease. Computational analyses, corroborated empirically, demonstrate that the top mRNA target of both microRNA-132 and microRNA-212 is TMEM106B; both microRNAs repress TMEM106B expression through shared microRNA-132/212 binding sites in the TMEM106B 3’UTR. Increasing TMEM106B expression to model disease results in enlargement and poor acidification of endo-lysosomes, as well as impairment of mannose-6-phosphate-receptor trafficking. Finally, endogenous neuronal TMEM106B co-localizes with progranulin in late endo-lysosomes, and TMEM106B over-expression increases intracellular levels of progranulin. Thus, TMEM106B is an FTLD-TDP risk gene, with microRNA-132/212 depression as an event which can lead to aberrant over-expression of TMEM106B, which in turn alters progranulin pathways. Evidence for this pathogenic cascade includes the striking convergence of two independent, genomic-scale screens on a microRNA:mRNA regulatory pair. Our findings open novel directions for elucidating miRNA-based therapies in FTLD-TDP.

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Clinical sequencing is expanding, but causal variants are still not identified in the majority of cases. These unsolved cases can aid in gene discovery when individuals with similar phenotypes are identified in systems such as the Matchmaker Exchange. We describe risks for gene discovery in this growing set of unsolved cases. In a set of rare disease cases with the same phenotype, it is not difficult to find two individuals with the same phenotype that carry variants in the same gene. We quantify the risk of false-positive association in a cohort of individuals with the same phenotype, using the prior probability of observing a variant in each gene from over 60,000 individuals (ExAC). Based on the number of individuals with a genic variant, cohort size, specific gene, and mode of inheritance, we calculate a p-value that the match represents a true association. A match in two of ten patients in MECP2 is statistically significant (p=0.0014), while a match in TTN would not reach significance, as expected (p>0.999). Finally, we analyze the probability of matching in clinical exome cases to estimate the number of cases needed to identify genes related to different disorders. We offer RD-Match, an online tool to mitigate the uncertainty of false-positive associations.

The influence of genetic background on driver mutations is well established; however, the mechanisms by which the background interacts with Mendelian loci remains unclear. We performed a systematic secondary-variant burden analysis of two independent Bardet-Biedl syndrome (BBS) cohorts with known recessive biallelic pathogenic mutations in one of 17 BBS genes for each individual. We observed a significant enrichment of trans-acting rare nonsynonymous secondary variants compared to either population controls or to a cohort of individuals with a non-BBS diagnosis and recessive variants in the same gene set. Strikingly, we found a significant over-representation of secondary alleles in chaperonin-encoding genes, a finding corroborated by the observation of epistatic interactions involving this complex in vivo.These data indicate a complex genetic architecture for BBS that informs the biological properties of disease modules and presents a model paradigm for secondary-variant burden analysis in recessive disorders.A persistent hurdle in interrogating the role of genetic background in human genetic disorders is our limited understanding of the properties and distribution of contributory alleles. The challenge is particularly acute in rare disorders, in which the allele frequency of both causal variants and secondary contributory alleles (i.e. alleles in loci other than the primary locus) is often low; as such population-based studies are hampered by the lack of statistical power. At the same time, transitioning from a single-gene-centric to a systems-based disease architecture defined by biological modules can inform causality, penetrance and expressivity 1 . Bardet-Biedl syndrome, a model ciliopathy, represents an opportunity to study secondary-variant burden. We and others have shown previously that BBS patients can carry secondary pathogenic variants in known BBS genes 2 . In rare examples, such alleles can modify penetrance 3 , whereas, more commonly, they are thought to modulate expressivity 4,5 . However, initial population-based studies have failed to detect an enrichment for secondary alleles in trans (i.e. alleles in loci other than the primary locus), suggesting that either some of the examples were exceptions, or that the incidence, distribution, and frequency of such alleles might be different than assumed a priori 6 . Here, we studied two BBS cohorts with unambiguous recessive pathogenic mutations in 17 established BBS genes to measure a) whether there is enrichment for secondary variants beyond the driver locus; and b) if so, whether the excess variation is concentrated within discrete disease modules or whether it is randomly distributed.