In both two cohorts, we targeted the variants in the coding region of the DNM1L gene (NM_001278466 ). The variants with a missing rate of >5% and deviations from Hardy–Weinberg equilibrium in controls (p < 0.05) were removed using PLINK v1.90. We annotated the gene regions (hg19 RefSeq), amino acid changes, and allele frequency of each variant in the Genomic Aggregation Database (gnomAD) and Exon Aggregation Consortium (ExAC) by ANNOVAR. Next, the functional impact of each nonsynonymous variant was predicted by ReVe (threshold, 0.7).
We categorized the variants according to the minor allele frequency (MAF) as common variants (MAF > 0.01) and rare variants (MAF < 0.01). Furthermore, we re-extracted the rare variants with MAF below 0.001 and performed gene analysis of rare variants with MAF below 0.01 and 0.001, respectively. According to predicted functions, all the rare nonsynonymous variants were classified into three variant groups: missense, potentially damaging missense (Dmis, ReVe score > 0.7), and loss of function variants (LoF stop gain/loss, frameshift, and splice site), and the sum of Dmis and LoF. After adjusting the abovementioned covariates in two cohorts, sequence kernel association test-optimal (SKAT-O) was applied to each cohort to assess the combined effect of rare variants and each variants group. Fisher's exact test was also done for common variants to validate the significant relationship between the common variants of DNM1L and PD. Moreover, logistic regression analysis based on an allele model was also performed by PLINK v1.90, and a p-value of < 0.05 was considered suggestive significant.
We categorized the variants according to the minor allele frequency (MAF) as common variants (MAF > 0.01) and rare variants (MAF < 0.01). Furthermore, we re-extracted the rare variants with MAF below 0.001 and performed gene analysis of rare variants with MAF below 0.01 and 0.001, respectively. According to predicted functions, all the rare nonsynonymous variants were classified into three variant groups: missense, potentially damaging missense (Dmis, ReVe score > 0.7), and loss of function variants (LoF stop gain/loss, frameshift, and splice site), and the sum of Dmis and LoF. After adjusting the abovementioned covariates in two cohorts, sequence kernel association test-optimal (SKAT-O) was applied to each cohort to assess the combined effect of rare variants and each variants group. Fisher's exact test was also done for common variants to validate the significant relationship between the common variants of DNM1L and PD. Moreover, logistic regression analysis based on an allele model was also performed by PLINK v1.90, and a p-value of < 0.05 was considered suggestive significant.
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