Genome sequencing analysis identifies new loci associated with Lewy body dementia and provides insights into its genetic architecture

Abstract

The genetic basis of Lewy body dementia (LBD) is not well understood. Here, we performed whole-genome sequencing in large cohorts of LBD cases and neurologically healthy controls to study the genetic architecture of this understudied form of dementia, and to generate a resource for the scientific community. Genome-wide association analysis identified five independent risk loci, whereas genome-wide gene-aggregation tests implicated mutations in the gene GBA. Genetic risk scores demonstrate that LBD shares risk profiles and pathways with Alzheimer's disease and Parkinson's disease, providing a deeper molecular understanding of the complex genetic architecture of this age-related neurodegenerative condition.

Extended Data Fig. 1. BIN1 and TMEM175 genotype-phenotype analysis

Relationship between BIN1 and TMEM175 genotypes and the presence of Alzheimer’s disease co-pathology in definite LBD cases. The color gradation refers to semi-quantitative pathological measures of neuritic plaques (assessed by CERAD method) and neurofibrillary tangles (assessed by Braak stage). Darker colors refer to higher burden of pathology. Homozygous BIN1 risk allele carriers (TT) were found to have significantly increased neurofibrillary tangle pathology compared to homozygous major allele carriers (CC; Fisher’s exact test P-value on Braak staging = 0.0002). Although the proportion of LBD cases that had high neuritic plaque burden was higher in homozygous risk allele carries compared to homozygous major allele carries, the difference between these groups was not statistically significant (P = 0.23). There was no association of TMEM175 risk allele dosage and Alzheimer’s disease co-pathology, though a trend toward lower Alzheimer’s disease co-pathology was observed among homozygous TMEM175 risk allele carriers.

Extended Data Fig. 2. Regional association plots

a-g, Regional association plots, local linkage disequilibrium, and recombination rates at the significantly associated LBD GWAS risk signals. Regional associations are plotted as a function of their genomic position, denoting the index variant by a red diamond. Single nucleotide variants or indels surrounding the index variant are color-coded to reflect the strength of linkage disequilibrium with the index variant based on pairwise r²-values in the study cohort (red, 1.0 ≥ r² ≥ 0.8; orange, 0.8 > r² ≥ 0.6; green 0.6 > r² ≥ 0.4; light blue, 0.4 > r² ≥ 0.2; dark blue, 0.2 > r² ≥ 0; gray, no r² value available). Transcript annotations according to the University of California Santa Cruz genome browser are depicted under each association plot.

Extended Data Fig. 3. Conditional analysis

a-f, Conditional analyses for all genome-wide significant GWAS signals are depicted. For each panel, the x-axis denotes the chromosomal position in build 38, and the y-axis indicates the association P-values on a −log₁₀ scale. The unconditioned GWAS signal is shown in the upper pane of each panel, while the lower pane illustrates the association results after correction for the index variant(s) at each respective signal. This analysis demonstrated two signals at the APOE locus (e, f). The locus name is based on the closest gene to the index variant.

Extended Data Fig. 4. Sensitivity analyses

a,b, Sensitivity analyses of colocalization between eQTLs regulating TMEM175 expression and LBD GWAS signals (a) and SNCA-AS1 expression and LBD GWAS signals (b). eQTLs for TMEM175 were derived from eQTL-Gen, while eQTLs for SNCA-AS1 were derived from PsychENCODE. Plots of prior (left) and posterior (right) probabilities for H₀-H₄ hypotheses across varying p₁₂ priors are shown. A dashed vertical line indicates the value of p₁₂ used in the initial analysis (p₁₂ = 5 × 10⁻⁶). The green shaded areas in these plots show the regions for which the posterior probability of H4 ≥ 0.90 would still be supported. Abbreviations: H0, hypothesis 0 (no association with either trait); H1, hypothesis 1 (association with trait 1, not with trait 2); H2, hypothesis 2 (association with trait 2, not with trait 1); H3, hypothesis 3 (association with trait 1 and trait 2, two independent SNPs); H4, hypothesis 4 (association with trait 1 and trait 2, one shared SNP).

Extended Data Fig. 5. GWAS variants correlate with increased SNCA-AS1 expression

Shown here are genome-wide significant SNPs that decrease risk for LBD and their correlation with increased SNCA-AS1 expression. a, Scatterplot of beta coefficients and association P-values (on a -log10 scale) for SNPs shared between the LBD GWAS (left) and PsychENCODE (right). The SNPs represented in this plot are those that are eQTLs regulating SNCA-AS1 expression. The top SNP in the LBD GWAS (as determined by the lowest association test P-value) is indicated in both scatterplots by a red point. The dashed line represents the cut-off for genome-wide significance (5 × 10⁻⁸). b, Scatterplot of SNPs shared between the LBD GWAS and PsychENCODE, which pass genome-wide significance in the LBD GWAS. Spearman’s rho (R) and associated P-value are displayed.

Extended Data Fig. 6. Tissue and cell-type specificity of SNCA-AS1 and TMEM175

a,b, Plot of SNCA-AS1 and TMEM175 specificity in 35 human tissues (GTEx dataset) (a) and seven broad categories of cell types derived from human middle temporal gyrus (Allen Institute for Brain Science dataset) (b). Tissues are colored by whether they belong to the brain. In all plots, tissues and cell types have been ordered by specificity.

Extended Data Fig. 7. Tissue and cell-specificity of SNCA-AS1 and SNCA

a,b, Plots of SNCA-AS1 and SNCA specificity in 35 human tissues (GTEx dataset) (a) and seven broad categories of cell types derived from human middle temporal gyrus (Allen Institute for Brain Science dataset) (b). Tissues are colored by whether they belong to the brain. In all plots, tissues and cell types have been ordered by specificity.

Extended Data Fig. 8. LBD polygenic risk score is associated with dementia severity

Dementia severity score proportions (measured by the Clinical Dementia Rating scale) at baseline evaluation relative to LBD polygenic risk score quintiles. LBD patients in the highest quintile had significantly more severe cognitive impairment at baseline compared to cases in the lowest quintile (χ² = 5.60, df = 1, test P-value = 0.009).

Extended Data Fig. 9. Principal components analysis and QQ plot

Quality control metrics of GWAS data. a, Population structure is shown by plotting the first two principal components of the study cohorts (n = 2,591 LBD cases and n = 4,027 controls) compared to the HapMap3 Genome Reference panel. b, Quantile-quantile (QQ) plot of single-variant associations depicting observed (y-axis) versus expected P-values (x-axis). The sample size adjusted genomic inflation factor λ1000 was 1.004.

Extended Data Fig. 10. Quality control metrics

This figure depicts quality control metrics of the genome data across study cohorts. a, Heterozygous-to-homozygous single nucleotide variant (SNV) ratios. b, Mean coverage across the study cohorts.

Fig. 1 |. Analysis workflow.

Schematic illustration of the analytical workflow.

Fig. 2 |. Genome-wide representation of common and rare variant associations in LBD.

a-c, Manhattan plots depicting the GWAS results (n = 2,591 cases and 4,027 controls; MAF > 1%) (a), the GWAS subanalysis of pathologically confirmed LBD cases only (n = 1,789) versus controls (n = 4,027) (b), and gene-based genome-wide SKAT-O test associations of rare missense variants (MAF ≤ 1%, MAC ≥ 3) (c). The x-axis denotes the chromosomal position for all 22 autosomes in hg38, and the y-axis indicates the association P-values on a −log₁₀ scale. Each dot in a and b indicates a single-nucleotide variant or indel, while each dot in c corresponds to a gene. Red dots highlight genome-wide significant signals, while suggestive variants are indicated with orange dots. A dashed line shows the conservative Bonferroni threshold for genome-wide significance. For a and b, the gene with the closest proximity to the top variant at each significant locus is listed. Green font was used to highlight known LBD risk loci, while black font indicates novel association signals.

Fig. 3 |. Regional association plots for eQTL and LBD GWAS colocalizations.

a,b, Regional association plots for eQTL (upper pane) and LBD GWAS signals (lower pane) in the regions surrounding TMEM175 (PPH4 = 0.99) (a) and SNCA-AS1 (PPH4 = 0.96) (b). The x-axis denotes the chromosomal position in hg19, and the y-axis indicates the association P-values on a −log₁₀ scale.

Fig. 4 |. Genetic risk scores from Alzheimer’s disease and Parkinson’s disease GWAS studies illustrate intersecting molecular genetic risk profiles with LBD.

Alzheimer’s disease and Parkinson’s disease genetic risk scores predict risk for LBD and highlight overlapping molecular risk profiles. a, Violin plots comparing z-transformed Alzheimer’s disease genetic risk score distributions in LBD cases, controls, and 100 random Alzheimer’s disease cases. b, Violin plots comparing z-transformed Parkinson’s disease genetic risk score distributions for LBD cases, controls, and 100 random Parkinson’s disease cases. The center line of each violin plot is the median, the box limits depict the interquartile range, and whiskers correspond to the 1.5x interquartile range. Abbreviations: GRS, genetic risk score; AD, Alzheimer’s disease; PD, Parkinson’s disease.

Fig. 5 |. Insights into LBD pathways based on polygenic risk score enrichment analysis.

Functional enrichment analyses of the LBD polygenic risk scores. The x-axis corresponds to the enrichment category in LBD cases compared to controls, and the y-axis shows the enrichment percentages of significant associations after multiple testing correction. The enrichment percentage refers to the percentage of input genes/variants that are within in a given pathway. Significant gene ontology (GO) enrichments for biological processes (BP, orange), cellular functions (CC, blue), molecular functions (MP, green), and pathways from WikiPathways (WP, pink) are shown. The size of each respective dot indicates the P-values on a −log₁₀ scale.