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Yang, Zhongan

https://orcid.org/0000-0002-2996-1708

A5087818688 | I161318765

Mayo Clinic

University of California, Los Angeles

Citations 2

Familial relatedness in genetic frontotemporal dementia cohorts: findings from the international Frontotemporal Dementia Prevention Initiative

Alzheimer's & Dementia | December 25, 2023 | Volume: 19 | Issue: S18 | Pages: No page available

10.1002/alz.078637

AbstractBackgroundGiven the rarity of genetic frontotemporal dementia (FTD), researchers across the world have come together to form the FTD Prevention Initiative (FPI) in an effort to improve prevention trials design. As this initiative begins to bring together large‐scale data from worldwide cohort series, including ALLFTD in North America and GENFI in Europe and Canada, it is critical for FPI to quantify the level of relatedness between all participants. Here we provide the most recent update to these ongoing analyses.MethodsGenome‐wide SNP genotyping data from 1,684 ALLFTD and 568 GENFI participants was used to perform lineage analyses using PLINK. Briefly, QC was performed similarly in all datasets to remove individuals with low call rate and filter autosomal SNPs for missingness, frequency, and deviation from Hardy‐Weinberg equilibrium. Genetic ancestry was inferred by projecting genotyped samples into the principal components of the 1000 Genomes reference panel, using R package bigsnpr. Overlapping ALLFTD and GENFI genotyping data was then used, in a two‐stage approach, to calculate pairwise identity‐by‐descent (IBD) estimates and KING coefficients, followed by family‐network identification and pedigree reconstruction using PRIMUS.ResultsFirst, we calculated IBD estimates among all participants by restricting pairs to those with estimates>0.1875 (up to second‐degree relatives). Overall, we identified a total of 292 second‐degree family networks, including 168 ALLFTD and 120 GENFI families, mostly associated with pathogenic variants in the 3 major FTD‐causing genes. We also identified 4 family networks with participants enrolled in both the ALLFTD and GENFI series, as well as several multi‐site families within the ALLFTD consortium. This first, overall approach allowed us to predict close relationships even between individuals with different ancestral backgrounds, including at least 4 confirmed admixed families. More distant relationships were also detected within ALLFTD and GENFI by performing ancestry‐based analysis among participants with estimated European ancestry, using the KING‐robust algorithm.ConclusionsThese lineage analyses allowed us to identify, otherwise unknown, close (and distant) relatives from different study sites, as well as within the ALLFTD and GENFI series. This dataset will be a crucial resource to increase statistical accuracy and power in upcoming collaborative FPI studies.
Inferring genetic relatedness in a large, multisite frontotemporal dementia series: Data from the ALLFTD consortium

Alzheimer's & Dementia | June 16, 2023 | Volume: 19 | Issue: S1 | Pages: No page available

10.1002/alz.068040

AbstractBackgroundThe ARTFL‐LEFFTDS Longitudinal Frontotemporal Lobar Degeneration (ALLFTD) research consortium is actively enrolling participants across 23 North American centers to characterize sporadic and familial frontotemporal dementia (FTD) and prepare for disease‐modifying clinical trials. The ability to identify, otherwise unknown, relatives among these participants is critical to rigorously build family structures for downstream clinical and genetic research studies.MethodsGenome‐wide SNP genotyping data from ALLFTD participants was used to perform lineage analyses using PLINK. Briefly, QC was performed to remove individuals with low call rate and filter autosomal SNPs for missingness, allele frequency, and deviation from Hardy‐Weinberg equilibrium, before pruning SNPs for linkage disequilibrium. Identity‐by‐descent (IBD) estimates were then calculated for determining relatedness, followed by family‐network identification and pedigree reconstruction using PRIMUS.ResultsAbout 46% of ALLFTD participants that were genotyped and passed QC (n = 1,453) had reported a family history, while 50% (n = 721) did not and were considered sporadic. We identified a total of 460 participants that had at least one relative who was second degree or closer (PI_HAT>0.1875) based on IBD sharing, resulting in 150 family networks. This included 9 participants who self‐identified as sporadic, demonstrating the utility of direct genetic characterization to determine familiality in FTD. Most of the predicted families were associated with disease causing variants in the 3 major FTD‐causing genes: 66 families with known C9orf72 repeat expansion carriers, 35 with MAPT (including 11 families with the variant historically known as p.P301L) and 30 with GRN pathogenic variant carriers, as well as 2 families with carriers of both a C9orf72 expansion and a GRN pathogenic variant. We also identified 5 families with carriers of pathogenic variants in other familial dementia genes (2 TARDBP, 2 VCP and 1 PSEN1), as well as 12 families with yet unknown genetic etiology.ConclusionsThis dataset sets up a crucial resource to increase statistical accuracy and power in downstream association studies using the clinical, neuropsychological, neuroimaging and biomarker data currently being generated by the ALLFTD consortium. It will also facilitate genetic studies aimed at novel gene discovery, and identification of haplotypes and genetic modifiers associated with the 3 major FTD causal genes.