A sociodemographic index identifies non-biological sex-related effects on insomnia in the Hispanic Community Health Study/Study of Latinos.

Background: Sex differences are related to both biological factors and the gendered environment. To untangle sex-related effects on health and disease it is important to model sex-related differences better. Methods: Data came from the baseline visit of the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), a longitudinal cohort study following 16,415 individuals recruited at baseline from four study sites: Bronx NY, Miami FL, San Diego CA, and Chicago IL. We applied LASSO penalized logistic regression of male versus female sex over sociodemographic, acculturation, and psychological factors jointly. Two "gendered indices", GISE and GIPSE, summarizing the sociodemographic environment (GISE, primary) and psychosocial and sociodemographic environment (GIPSE, secondary) associated with sex, were calculated by summing these variables, weighted by their regression coefficients. We examined the association of these indices with insomnia derived from self-reported symptoms assessed via the Women Health Initiative Insomnia Rating Scale (WHIIRS), a phenotype with strong sex differences, in sex-adjusted and sex-stratified analyses. All analyses were adjusted for age, Hispanic/Latino background, and study center. Results: The distribution of GISE and GIPSE differed by sex with higher values in male individuals, even when constructing and validating them on separate, independent, subsets of HCHS/SOL individuals. In an association model with insomnia, male sex was associated with lower likelihood of insomnia (odds ratio (OR)=0.60, 95% CI (0.53, 0.67)). Including GISE in the model, the association was slightly weaker (OR=0.63, 95% CI (0.56, 0.70)), and weaker when including instead GIPSE in the association model (OR=0.78, 95% CI (0.69, 0.88)). Higher values of GISE and of GIPSE, more common in male sex, were associated with lower likelihood of insomnia, in analyses adjusted for sex (per 1 standard deviation of the index, GISE OR= 0.92, 95% CI (0.87, 0.99), GIPSE OR=0.65, 95% CI (0.61, 0.70)). Conclusions: New measures such as GISE and GIPSE capture sex-related differences beyond binary sex and have the potential to better model and inform research studies of health. However, such indices do not account for gender identity and may not well capture the environment experienced by intersex and non-binary persons.

Sex differences in methylation profiles are apparent in medulloblastoma, particularly among SHH tumors.

Background: Medulloblastoma, the most common malignant pediatric brain tumor, displays marked sex differences in prevalence of the four main molecular subgroups: SHH, WNT, Group 3 and Group 4. Males are more frequently diagnosed with SHH, Group 3 and 4 tumors, which have worse prognoses than WNT tumors. Little is known about sex differences in methylation profiles within subgroups. Methods: Using publicly available methylation data (Illumina HumanMethylation450K array), we compared beta values for males versus females. Differentially methylated positions (DMP) by sex within medulloblastoma subgroups were identified on the autosomes. DMPs were mapped to genes and Reactome pathway analysis was run by subgroup. Kaplan-Meier survival curves (Log-Rank p-values) were assessed for each sex within subgroup. MethylCIBERSORT was used to investigate the tumor microenvironment using deconvolution to estimate the abundances of immune cell types using DNA methylation data. Results: There were statistically significant differences in sex by medulloblastoma subgroups (chi-squared p-value=0.00004): Group 3 (n=144; 65% male), Group 4 (n=326; 67% male), SHH (n=223; 57% male) and WNT (n=70; 41% male). Females had worse survival than males for SHH (p-value=0.02). DMPs by sex were identified within subgroups: SHH (n=131), Group 4 (n=29), Group 3 (n=19), and WNT (n=16) and validated in an independent dataset. Unsupervised hierarchical clustering showed that sex-DMPs in SHH did not correlate with other tumor attributes. Ten genes with sex DMPs (RFTN1, C1orf103, FKBP1B, COL25A1, NPDC1, B3GNT1, FOXN3, RNASEH2C, TLE1, and PHF17) were shared across subgroups. Significant pathways (p<0.05) associated with DMPs were identified for SHH (n=22) and Group 4 (n=4) and included signaling pathways for RET proto-oncogene, advanced glycosylation end product receptor, regulation of KIT, neurotrophic receptors, NOTCH, and TGF-ß. In SHH, we identified DMPs in four genes (CDK6, COL25A1, MMP16, PRIM2) that encode proteins which are the target of therapies in clinical trials for other cancers. There were few sex differences in immune cell composition within tumor subgroups. Conclusion: There are sexually dimorphic methylation profiles for SHH medulloblastoma where survival differences were observed. Sex-specific therapies in medulloblastoma may impact outcomes.

Global variation in young adult central nervous system tumor incidence by region, age, and sex from 1988 to 2012.

BACKGROUND: Central nervous system (CNS) tumors result in tremendous morbidity and mortality. Incidence of CNS tumors in young adults is less studied. It is unknown how young adult CNS tumor incidence has changed globally in recent decades. METHODS: We used Cancer Incidence in Five Continents (CI5) data (1988-2012) to estimate incidence rates (IR), average annual percent change in incidence (AAPC; 95% confidence intervals [95% CI]), and male-to-female incidence rate ratios (IRR; 95% CI) by six histologies and age at diagnosis (20-29years, 30-39years). Tumors were classified as astrocytic, medulloblastoma, ependymal, oligodendroglial, meninges, and other embryonal. Geographic regions were defined using the United Nations Statistics Division geoscheme. RESULTS: There were 78,240 CNS tumor cases included. 20-29-year-old (yo) rates were lower than 30-39 yo in most regions for astrocytic, oligodendroglial and ependymal tumors. Globally, astrocytic tumor incidence decreased (20-29 yo AAPC: - 0.70; 95% CI: - 1.32, - 0.08) while incidence increased for oligodendroglial (20-29 yo AAPC: 3.03; 95% CI: 1.57-4.51; 30-39 yo AAPC: 2.67; 95% CI: 0.79-4.58), ependymal (20-29 yo AAPC: 1.16; 95% CI: 0.31-2.03; 30-39 yo AAPC: 2.29; 95% CI: 1.14-3.46), medulloblastoma (30-39 yo AAPC: 0.6; 95% CI: 0.04-1.24) and tumors of the meninges (20-29 yo AAPC: 1.55; 95% CI: 0.04-3.07). There was a 20-40% male incidence excess in all histologies except for meninge tumors (30-39 yo IRR: 0.71; 95% CI: 0.61, 0.84). CONCLUSIONS: Incidence of oligodendroglial and ependymal tumors increased globally in 20-39 yo suggesting better diagnoses or changes in risk factors. Males had a higher incidence of CNS tumors for most tumors studied and in most regions.

Racial/ethnic and sex differences in young adult malignant brain tumor incidence by histologic type.

BACKGROUND: Brain tumors are among the top four cancers in young adults. We assessed important windows of tumor development and examined the interplay of race/ethnicity, age, and sex in young adult brain tumor incidence. METHODS: Using SEER 18 data (2000-2017), incidence rates were estimated by Poisson regression in individuals aged 20-39 years at diagnosis. Incidence rate ratios (IRR) and 95% confidence intervals (95% CI) were estimated by race/ethnicity, sex and age for 12 malignant histologies. RESULTS: White incidence for all histologies was higher (White vs. Black IRR: 2.09, 95% CI: 1.94, 2.24; White vs Asian Pacific Islander IRR: 1.88, 95% CI: 1.75, 2.03; White vs Hispanic IRR: 1.70, 95% CI: 1.62, 1.78; White vs American Indian IRR: 1.40, 95% CI: 1.14, 1.73). Minority groups had higher lymphoma incidence (White vs Black IRR: 0.32, 95% CI: 0.25, 0.40, White vs Hispanic HR: 0.55, 95% CI: 0.44, 0.68). Males had higher incidence than females for all histologies (IRR: 1.36, 95% CI: 1.31, 1.41). Male rates were highest for lymphoma (male-to-female [MF] IRR: 2.00, 95% CI: 1.65, 2.42) and glioblastoma (MF IRR: 1.61, 95% CI: 1.48, 1.75). The male excess in incidence was similar by race/ethnicity and increased with age (20-24-year-old IRR: 1.18, 95% CI: 1.07, 1.29; 35-39-year-old IRR: 1.44, 95% CI: 1.35, 1.54). CONCLUSIONS: A White race and male incidence excess was observed among brain tumors. IMPACT: The male excess was similar by race/ethnicity and increased with age suggesting male sex may be an intrinsic risk factor for brain tumor development.