Phenoconversion and disease progression observed in mutation carriers of familial Frontotemporal Lobar Degeneration in the ALLFTD Consortium

Background The ARTFL‐LEFFTDS Longitudinal Frontotemporal Lobar Degeneration (ALLFTD) study is designed to characterize both sporadic and familial FTLD (f‐FTLD) through annual detailed clinical, neuropsychological, biomarker, and neuroimaging assessments to capture disease onset and trajectory in preparation for therapeutic trails in FTLD. Transitions from asymptomatic to mild disease, or from mild to overt, may reveal critical windows for intervention. Method 169 f‐FTLD participants carrying mutations in the main FTLD‐associated genes (79 C9orf72; 37 GRN; 53 MAPT) with at least two clinical assessments were included for analysis of phenoconversion from asymptomatic or mild disease. [CDRÒ + NACC FTLD global scores (Miyagawa et al, 2020) were used to define baseline status at first visit: “asymptomatic” = 0 and “mild” = 0.5. Conversion was defined as “partial” (asymptomatic to mild), “definite” (asymptomatic to overt [CDRÒ + NACC FTLD > = 1) and “mild to overt” (0.5 to > = 1). Result Definite conversion occurred most often in MAPT mutation carriers, with 5/43 asymptomatic carriers transitioning through mild to overt across multiple visits. Definite conversion was also seen in 2/65 C9orf72 expansion carriers and 1/30 GRN mutation carriers. All definite converters were assessed as mild (CDRÒ + NACC FTLD = 0.5) for at least one intermediate visit; definite conversion was observed from 2‐4 years from initial assessment. Partial conversions also occurred in all three genetic groups (MAPT: 6; C9orf72: 5; GRN: 5). Further conversion is expected to be observed in these participants in additional follow‐up visits. C9orf72 expansion carriers were less likely to progress from a baseline of mild to overt (3/14) than GRN carriers (4/6) or MAPT (7/10). Conclusion Longitudinal assessment through natural history studies can capture early phenoconversion in carriers of FTLD‐associated genetic mutations; corresponding imaging, cognitive, and biomarker profiles captured may provide insights into disease mechanisms and trajectories.