A Novel Genetic Marker for the C9orf72 Repeat Expansion in the Finnish Population

Cohorts, genotyping, and imputations of EADB samples, and clinical endpoints

This study includes GWAS data from the EADB and the FinnGen database. EADB data were processed as previously described [13]. Finnish iNPH patients included in the EADB GWAS were diagnosed according to published guidelines and procedures [14, 15]. C9_exp genotyping was performed using repeat-primed PCR and amplicon length analysis [3]. Previous studies have suggested a pathological threshold of  > 30 units [3, 6] or  > 45 units [16] for the C9_exp. However, smaller repeats of < 30 units may also associate with disease [4 , 17]. In these studies, the minimum lengths of the C9_exp have been identified as 7 [4] and 17 [16, 17] repeats on the longer allele. Here, we chose a threshold of 15 repeats to define individuals positive for the C9_exp. The iNPH cohort contains 41 C9_exp carriers [7 full-length (> 60 repeats) and 34 intermediate C9_exp carriers (15–30 repeats)] and 801 controls (< 15 repeats). Forty-eight percent of C9_exp carriers and controls were male.

Detailed information of the FinnGen data is described at https://www.finngen.fi/fi. Genome and clinical data from 218,792 individuals were obtained from FinnGen study data release 5. Clinical diagnoses were derived from the International Statistical Classification of Diseases and Related Health Problems, version 10 (ICD-10) codes in Finnish national hospital registries and cause-of-death registry as part of FinnGen project. UK Biobank data were used for validation of the identified SNPs and haplotypes.

Generation of risk haplotypes associating with C9_exp

Trans-Omics for Precision Medicine (TOPMed) imputed genotype data from EADB consortium was used [13]. Genotypes were phased with Eagle v2.4105 and imputed with Minimac4 v4-1.0.2. Only SNPs having Hardy-Weinberg equilibrium p > 10^–5 and imputation quality greater than 0.6 were considered. The imputation quality score for rs139185008 was 0.75. The previously published 20-SNP Finnish risk haplotype [12] was used to test for association with the C9_exp (iNPH cohort) and clinical diagnoses (“motor neuron disease” for ALS, “circumscribed brain atrophy” for FTLD; FinnGen). Additional upstream and downstream SNPs were added to create longer haplotypes that were able to distinguish C9_exp carriers better from non-carriers. The SNP selection was conducted based on a side by side inspection of an individual C9_exp carrier and non-carrier haplotypes of the phased and imputed most probable genotype data. Minor and major alleles included in the haplotypes are presented in Supplementary Table 1.

Analysis of SNP and haplotype association with C9_exp and clinical endpoints

Both LD-statistics (D’) and case vs. control logistic regression analysis with covariates were conducted on pre-processed imputed genotypes using PLINK software (version 1.9) [18]. For iNPH cohort, only principal component (PC) 1–2, and for FinnGen PC1-5 were used as covariates. UK Biobank data were extracted through http://big.stats.ox.ac.uk/variant/9:27491942-T-C and http://big.stats.ox.ac.uk/pheno/traits_011.

Data presentation

Manhattan and regional association plots were drawn using LocusZoom software (v0.12.0). For LD calculation, European reference population was used. Images were modified using LibreOffice Draw (version: 6.0.2.1). Bar graphs and geographical plot of minor allele frequencies (MAFs) were generated, and Pearson’s Chi-square test on minor versus major allele counts among Finnish regions was performed using RStudio software (version: 1.1.463) and ggplot2 [19] and geofi packages [20].

Data availability

Data are available on reasonable request from the corresponding authors. Due to privacy policies, the data are not publicly available.

Ethics statement

All experimental procedures complied with the standards of the Declaration of Helsinki. The Ethics Committee of Hospital District of Northern Savo approved the iNPH study and all patients provided an informed consent. Patients and controls in FinnGen provided informed consent for biobank research, based on the Finnish Biobank Act (https://www.finngen.fi/fi). All DNA samples and data were pseudonymized (iNPH cohort and FinnGen cohort).

C9_exp associates with SNPs near MOB3B and C9orf72 genes

Based on genotype data obtained from a global screening array, SNP association analysis was performed in a well-characterized iNPH patient cohort, comprising intermediate (15–30) and full-length (> 60 repeats) C9_exp carriers (n = 41) who were compared to non-carriers (< 15 repeats, n = 801). Except for two SNPs, all significantly C9_exp-associated SNPs (p < 5×10^–8) were located on chromosome 9 (Fig. 1A). Several of these were close or within the MOB kinase activator 3B (MOB3B) or C9orf72 genes, spanning an approx. 94 kb region, and showed a strong linkage disequilibrium (LD) (r²≥0.8) with the reference SNP rs3849942 (Fig. 1B), a previously reported surrogate marker for the chromosome 9p risk haplotype [2, 12]. Interestingly, rs139185008 (odds ratio, OR = 39.4, 95%CI [17.2–90.5], p = 4.6×10^–18), localizing within a recombination-poor region 81 541 bp upstream of the C9_exp, showed the strongest single SNP association with C9_exp carriership. Also, rs139185008 (MAF 0.016) was in complete LD (D’ = 1.00) with the reference SNP rs3849942 (MAF 0.17), which showed a weaker association with C9_exp carriership (OR 8.44, 95%CI [4.99–140.29], p = 2.0×10^–15). Importantly, rs139185008 was highly abundant in C9_exp carriers (MAF for full-length and intermediate carriers = 0.21 and 0.19, respectively), but rare in non-carriers (< 15 repeats, MAF = 0.008). Several C9_exp-associated haplotypes were significantly overrepresented in C9_exp carriers as compared to non-carriers in the iNPH cohort (Table 1). rs139185008 was part of the haplotypes 2, 5, 6, 8, and 10 showing the most prominent risk effects (OR > 42.0). Moreover, as compared to the previously reported 20-SNP Finnish risk haplotype, including, e.g., rs868856, rs7046653, rs2814707, rs3849942, and rs774359 [12] (Fig. 1B), the inclusion of rs139185008 to haplotypes (“haplo”) 2, 5, 6, 8, and 10 markedly improved the specificity to identify C9_exp carriers from non-carriers in the iNPH cohort (Table 1, Supplementary Table 1), e.g., the OR for haplotype 2 (OR = 11.33, 95%CI [6.38–20.14], p = 1.28×10^–16) substantially increased after the inclusion of rs139185008 (OR = 42.74, 95%CI [18.35–99.53], p = 3.16×10^–18).

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Fig. 1

SNPs associating with the C9orf72 repeat expansion in iNPH cohort locate near the MOB3B and C9orf72 genes. Manhattan plot of genome-wide association (GWA) of SNPs associated with the C9orf72 expansion in a Finnish iNPH cohort. Chromosome numbers are indicated below the x-axis (A). Regional association plot of chromosome 9 locus, which contained significant association from the GWA study. SNPs of the previously described Finnish risk haplotype [12] and rs139185008 (arrow) are indicated above the plot. Significantly associated SNPs are indicated in bold. Linkage disequilibrium is indicated as color-coded r² values. Recombination rates are depicted by continuous line. The reference variant rs3849942 is shown as a diamond (B). Gray lines indicate significance level (p < 5×10^–8). iNPH, idiopathic normal pressure hydrocephalus; SNP, single nucleotide polymorphism.

Rs139185008 strongly associates with FTLD and ALS in FinnGen

Next, we unbiasedly examined in the FinnGen database which clinical diagnoses associate with the SNPs and haplotypes identified in the iNPH cohort. The FinnGen database contains comprehensive genome-wide genotype data and life-long medical history from > 200,000 Finns. However, FinnGen does not include genetic data on complex genomic alterations, such as C9_exp. rs139185008 and haplotypes 2, 5, 6, 8, and 10 containing the minor allele of rs139185008 strongly associated with ALS and FTLD (Table 1). In comparison, the previously reported 20-SNP Finnish risk haplotype [12] showed a weaker association with ALS and FTLD (haplo 2, Table 1). In FinnGen, rs139185008 was the top SNP that associated with ALS and FTLD, confirming the result obtained in the iNPH GWAS (Fig. 1B). Importantly, rs139185008 also significantly associated with ALS in UK Biobank (p = 9.0×10^–8), but it was not among the top SNPs associated with ALS (beta value = –0.4; p values≤1.2×10^–18; Supplementary Figure 1).

Rs139185008 is regionally enriched to South-Eastern Finland

Finally, we used FinnGen data to calculate the MAF of the rs139185008 according to the region of birth in Finland (Fig. 2). Geographically, the rs139185008 minor allele showed the highest prevalence in Southern Savonia (MAF = 0.025) and the lowest in Ostrobothnia (MAF = 0.008) (Fig. 2). Pearson’s Chi-square test of the frequency of rs139185008 minor allele revealed significant differences in the geographic distribution of rs139185008 in Finland (p < 2.2×10^–16, χ² = 282.43, df = 18).

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Fig. 2

Geographical distribution of rs139185008 minor allele frequencies in different regions in Finland. Minor allele frequencies (MAF) of rs139185008 in Finland. Pearson’s Chi-square test revealed statistically significant deviation (p < 2.2×10^–16, χ² = 282.43, df = 18) of the geographical distribution of the minor allele counts of rs139185008. Genotyped population sizes are given for each region. Mean MAF for all regions is indicated as black vertical line (A). MAF of rs139185008 within Finnish regions showed geographical clustering of high (dark magenta) and low (white) frequencies (B).