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. 2019 Jul:127:492-501.
doi: 10.1016/j.nbd.2019.04.004. Epub 2019 Apr 3.

Heritability and genetic variance of dementia with Lewy bodies

Rita Guerreiro  1 Valentina Escott-Price  2 Dena G Hernandez  3 Celia Kun-Rodrigues  4 Owen A Ross  5 Tatiana Orme  1 Joao Luis Neto  1 Susana Carmona  1 Nadia Dehghani  1 John D Eicher  6 Claire Shepherd  7 Laura Parkkinen  8 Lee Darwent  9 Michael G Heckman  10 Sonja W Scholz  11 Juan C Troncoso  12 Olga Pletnikova  12 Ted Dawson  13 Liana Rosenthal  13 Olaf Ansorge  8 Jordi Clarimon  14 Alberto Lleo  14 Estrella Morenas-Rodriguez  15 Lorraine Clark  16 Lawrence S Honig  16 Karen Marder  16 Afina Lemstra  17 Ekaterina Rogaeva  18 Peter St George-Hyslop  19 Elisabet Londos  20 Henrik Zetterberg  21 Imelda Barber  22 Anne Braae  22 Kristelle Brown  22 Kevin Morgan  22 Claire Troakes  23 Safa Al-Sarraj  23 Tammaryn Lashley  24 Janice Holton  24 Yaroslau Compta  25 Vivianna Van Deerlin  26 Geidy E Serrano  27 Thomas G Beach  27 Suzanne Lesage  28 Douglas Galasko  29 Eliezer Masliah  30 Isabel Santana  31 Pau Pastor  32 Monica Diez-Fairen  32 Miquel Aguilar  32 Pentti J Tienari  33 Liisa Myllykangas  34 Minna Oinas  35 Tamas Revesz  24 Andrew Lees  24 Brad F Boeve  36 Ronald C Petersen  36 Tanis J Ferman  37 Neill Graff-Radford  38 Nigel J Cairns  39 John C Morris  39 Stuart Pickering-Brown  40 David Mann  40 Glenda M Halliday  41 John Hardy  4 John Q Trojanowski  26 Dennis W Dickson  5 Andrew Singleton  42 International Parkinson's Disease Genomics ConsortiumDavid J Stone  43 Jose Bras  44
Affiliations

Heritability and genetic variance of dementia with Lewy bodies

Rita Guerreiro et al. Neurobiol Dis. 2019 Jul.

Abstract

Recent large-scale genetic studies have allowed for the first glimpse of the effects of common genetic variability in dementia with Lewy bodies (DLB), identifying risk variants with appreciable effect sizes. However, it is currently well established that a substantial portion of the genetic heritable component of complex traits is not captured by genome-wide significant SNPs. To overcome this issue, we have estimated the proportion of phenotypic variance explained by genetic variability (SNP heritability) in DLB using a method that is unbiased by allele frequency or linkage disequilibrium properties of the underlying variants. This shows that the heritability of DLB is nearly twice as high as previous estimates based on common variants only (31% vs 59.9%). We also determine the amount of phenotypic variance in DLB that can be explained by recent polygenic risk scores from either Parkinson's disease (PD) or Alzheimer's disease (AD), and show that, despite being highly significant, they explain a low amount of variance. Additionally, to identify pleiotropic events that might improve our understanding of the disease, we performed genetic correlation analyses of DLB with over 200 diseases and biomedically relevant traits. Our data shows that DLB has a positive correlation with education phenotypes, which is opposite to what occurs in AD. Overall, our data suggests that novel genetic risk factors for DLB should be identified by larger GWAS and these are likely to be independent from known AD and PD risk variants.

Keywords: Dementia; Genetic correlation; Genetic variance; Lewy bodies.

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Conflict of interest statement

Conflict of Interest Statement

Dr Shepherd and Halliday from Australia report no conflict of interests for this work.

Figures

Figure 1:
Figure 1:
Estimate of the DLB variance explained by HRC-imputed variants by MAF and LD. Segmental LD score increases from the 1st to 4th quartiles. Negative scores are not shown for simplicity but are present in Supplementary Table 1. The estimates of variance explained are from the GREML-LDMS analyses of fitting all the 24 genetic components simultaneously.
Figure 2:
Figure 2:
Proportion of variance of DLB case-control status explained by PRSs from AD (A), AD excluding the APOE locus (B), PD (C) and PD excluding the GBA locus (D). The bars represent PRSs calculated for 9 subsets of markers at different p-value thresholds in the original GWAS publications. Best scores for each PRS are presented in (D). R2: Nagelkerke’s pseudo-R2; Threshold: P-value threshold in original GWAS.
Figure 3:
Figure 3:
Correlation scores with p-value <0.01 in DLB. Shown are also the scores for those same traits in PD and AD.

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