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Figure S2. Relationship between BMI and SpO2 at sea level in 46 Japanese male students. (PDF 101Â kb)

Figure S4. Relationship between SpO2 and perfusion index at 60 min (equivalent to 4000 m) for rs12097901 (a) and rs2790859 (b). Red characters represent highlander alleles. Blue line and gray band represent a regression line and its 95% confidence interval, respectively. Circle colors indicate genotypes of each SNP. The mean slope of the regression line was 0.011. Linear regression analysis showed no significant correlation (r2 = 0.011, P = 0.481). ANCOVA also showed no significant differences in the regression coefficient between genotypes (F(2, 40) = 2.20, P = 0.124 for rs12097901; F(2, 40) = 0.69, P = 0.509 for rs2790859) and in the adjusted mean values (F(2, 42) = 1.29, P = 0.285 for rs12097901; F(2, 42) = 1.08, P = 0.348 for rs2790859). (PDF 227 kb)

Figure S1. Linkage disequilibrium plot of 1504 biallelic sites across a ~ 399-kb genomic region at 1q42.2, based on datasets from JPT (Japanese in Tokyo, Japan) in the 1000 Genomes Project database. The position of SNPs examined is shown by the green arrow. The haplotype block was defined by the method of Gabriel et al. [36]. The genetic variants with the minor allele frequency of

Figure S5. Relationship between SpO2 and respiratory exchange ratio at 60 min (equivalent to 4000 m) for rs12097901 (a) and rs2790859 (b). Red characters represent highlander alleles. Blue line and gray band represent a regression line and its 95% confidence interval, respectively. Circle colors indicate genotypes of each SNP. The mean slope of the regression line was 0.002. Linear regression analysis showed no significant correlation (r2 = 0.012, P = 0.474). ANCOVA also showed no significant differences in the regression coefficient between genotypes (F(2, 40) = 0.19, P = 0.825 for rs12097901; F(2, 40) = 0.98, P = 0.384 for rs2790859) and in the adjusted mean values (F(2, 42) = 0.59, P = 0.557 for rs12097901; F(2, 42) = 0.17, P = 0.840 for rs2790859). (PDF 215 kb)

Figure S3. Relationship between SpO2 and minute ventilation at 60 min (equivalent to 4000 m) for rs12097901 (a) and rs2790859 (b). Red characters represent highlander alleles. Blue line and gray band represent a regression line and its 95% confidence interval, respectively. Circle colors indicate genotypes of each SNP. The mean slope of the regression line was − 0.018. Linear regression analysis showed no significant correlation (r2 = 0.001, P = 0.818). ANCOVA also showed no significant differences in the regression coefficient between genotypes (F(2, 40) = 1.21, P = 0.309 for rs12097901; F(2, 40) = 0.04, P = 0.961 for rs2790859) and in the adjusted mean values (F(2, 42) = 2.97, P = 0.062 for rs12097901; F(2, 42) = 0.11, P = 0.894 for rs2790859). (PDF 230 kb)

Table S2. Haplotype and diplotype frequencies of five SNPs around EGLN1 in 46 Japanese subjects. (PDF 71Â kb)

Background: Some studies have reported gender differences in N170, a face-selective event-related potential (ERP) component. This study investigated gender differences in N170 elicited under oddball paradigm in order to clarify the effect of task demand on gender differences in early facial processing. Findings: Twelve males and 10 females discriminated targets (emotional faces) from non-targets (emotionally neutral faces) under an oddball paradigm, pressing a button as quickly as possible in response to the target. Clear N170 was elicited in response to target and non-target stimuli in both males and females. However, females showed more negative amplitude of N170 in response to target compared with non-target, while males did not show different N170 responses between target and non-target. Conclusions: The present results suggest that females have a characteristic of allocating attention at an early stage when responding to faces actively (target) compared to viewing faces passively (non-target). This supports previous findings suggesting that task demand is an important factor in gender differences in N170.