The Promises and Pitfalls of Sex Difference Research

It’s been hypothesised that XXY’s are biological females dressed in male clothing, that being so we ask you keep in mind when reading how an XXY experience might have greater similarity to females than males, of course none of this would be necessary if researches were to include Intersex as a variable. Still comparing the binary sexes is a step in the right direction but should by no means be the final step.

The XXY Project

In 2016 the USA National Institutes of Health (NIH) mandated that all pre-clinical research must include sex as a biological variable (SABV), unless strongly justified otherwise. This has substantially increased attention to sex differences research, with good reason. Studying how biological sex contributes to our health can help understanding of disease etiology, manifestation, progression, and treatment. Indeed, males are more likely to be diagnosed with autism spectrum disorders or develop Parkinson’s disease whereas females are more likely to be diagnosed with major depressive disorder, anxiety disorders, autoimmune disease, and multiple sclerosis.

Sex differences are also noted in specific disease subsets, thus more females than males display the relapsing-remitting type of multiple sclerosis than men. Similarly, whereas the incidence of epilepsy is higher in males than females, only women are susceptible to a catamenial epilepsy, where seizures are tied to the menstrual cycle, and up to 70% of females with epilepsy show a variant of catamenial type. Perhaps less well known, there are also sex differences in the timing or onset of neuropsychiatric disorders. Onset of obsessive compulsive disorder is more likely to occur in early adolescence for males but during the perinatal period for females.

Even when prevalence of disease shows no sex bias, such as in schizophrenia, there can be profound differences in timing onset. Males are more likely to present with schizophrenia as teens, but females are more likely to present a couple of years later than males with a secondary peak in middle-age. Each of these examples gives us important clues on the nature of the disease. Yet, sex differences in onset and prevalence are rarely explored despite that studying these sex differences could yield powerful clinical and pre-clinical models of disease, and clues to disease etiology and pathology.

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Mortality in Patients with Klinefelter Syndrome in Britain: A Cohort Study

Photo Credit: Martin Adams

47XXY also known as Klinefelter’s Syndrome is a numerical chromosome variation, characterised by the presence of one or more extra X chromosomes. It occurs in about 1.5 per 1000 of the male population. The clinical syndrome was initially described in 1942, and the chromosome constitution was discovered in 1959. Characteristically, the patients have hypogonadism and elevated gonadotropin levels, and various other hormonal and physical abnormalities occur. There has been limited information about long-term mortality risks, however, because of the lack of large cohort (follow-up) studies. The only such published studies have been a cohort of 466 men from a Scottish register, later extended to two other centres with a total of 695 men, and a cohort of 781 men from Denmark. To enable more detailed analyses, based on much larger numbers, we assembled a cohort of cases of Klinefelter syndrome diagnosed in Britain for as long as records are held by the cytogenetics centres in the country and followed up the cohort for mortality, for periods of up to 40 years.

For each person in the cohort, we computed person-years of follow-up by 5-yr age group, calendar year, and country (England and Wales vs. Scotland), beginning from the date of cytogenetic diagnosis and ending at June 30, 2003, or the 85th birthday, date of death, or other loss to follow-up, whichever was earliest. Follow-up was censored at age 85 because at older ages than this, national (i.e. expected) mortality rates are not available by 5-yr age group, and the certified cause of death is often inaccurate. We calculated expected cause-specific mortality in the cohort by multiplying the age-, calendar years, and country-specific person-years at risk in the cohort by the corresponding national mortality rates for men. Standardized mortality ratios (SMRs) were then calculated as the ratio of observed to expected deaths, and 95% confidence intervals (CIs) for the SMRs were calculated assuming a Poisson distribution (8). Tests for trend and for the difference between SMRs were conducted as described by Breslow and Day (8). Significance tests were two-sided. Absolute excess risks were calculated by subtracting the expected from the observed numbers of deaths and dividing by person-years at risk.

We subdivided the subjects for analysis by the number of sex chromosomes, whether mosaicism was present, and if so, the constitution of the non-Klinefelter component. Where information was available for mosaics on the numbers of cells diagnosed with each mosaic component, we designated the subject as mosaic only if more than one cell had been counted with each component. We did not have direct information for the study subjects on whether mosaicism was congenital or acquired, but as a rough proxy for this [because the prevalence of acquired mosaicism rises with age (9)], we conducted separate analyses for mosaics diagnosed before age 45 yr and those diagnosed at older ages.

To assess, as far as possible, whether bias might account for certain of the results, we conducted several subanalyses of risks in subdivisions by birth year, risks omitting follow-up and deaths in the early years after cytogenetic diagnosis, and risks omitting cohort members recorded by the Medical Research Council Human Genetics Unit.

Results and further reading