Low testosterone at age 31 associates with maternal obesity and higher body mass index from childhood until age 46: A birth cohort study

BACKGROUND

Low testosterone (T) levels in men associate with increased risks of obesity, type 2 diabetes, metabolic syndrome, and cardiovascular diseases. However, most studies are cross-sectional with follow-up-time < 10 years, and data on early growth are limited.

OBJECTIVE

To compare prenatal factors and body mass index (BMI) development from birth to age 46 in relation to low T at age 31.

MATERIALS AND METHODS

Men with low T (T < 12.1 nmol/L, n = 132) and men with normal T at age 31 (n = 2561) were derived from the Northern Finland Birth Cohort 1966. Prenatal factors, longitudinal weight and height data from birth to age 14, and cross-sectional weight and height data at ages 31 and 46, and waist-hip-ratio (WHR) and T levels at age 31 were analyzed. Longitudinal modeling and timing of adiposity rebound (AR, second BMI rise at age 5-7 years) were calculated from fitted BMI curves. Results were adjusted for mother's pre-pregnancy BMI and smoking status, birth weight for gestational age, alcohol consumption, education level, smoking status, and WHR at age 31.

RESULTS

Neither gestational age nor birth weight was associated with low T at age 31; however, maternal obesity during gestation was more prevalent among men with low T (9.8% vs. 3.5%, adjusted aOR: 2.43 [1.19-4.98]). Men with low T had earlier AR (5.28 vs. 5.82, aOR: 0.73 [0.56-0.94]) and higher BMI (p < 0.001) from AR onward until age 46. Men with both early AR and low T had the highest BMI from AR onward.

CONCLUSIONS

In men, maternal obesity and early weight gain associate with lower T levels at age 31, independently of adulthood abdominal obesity. Given the well-known health risks related to obesity, and the rising prevalence of maternal obesity, the results of the present study emphasize the importance of preventing obesity that may also affect the later reproductive health of the offspring.

Polycystic ovary syndrome and leukocyte telomere length: cross-sectional and longitudinal changes

OBJECTIVE

Telomeres are DNA-protein complexes that protect chromosome ends from DNA damage and are surrogate biomarkers of cellular aging. Current evidence, almost entirely from cross-sectional observations, supports negative associations between leukocyte telomere length (LTL) and adverse lifestyle factors and cardiometabolic risk factors. Polycystic ovary syndrome (PCOS), the most common gynecological endocrine disorder, is associated with inflammation and oxidative stress, both factors associated with accelerated telomere attrition. We therefore hypothesized that LTL would be shorter and decrease more rapidly in women with PCOS in comparison to a control population.

DESIGN

This is a population-based cohort study comprising women of Northern Finland Birth Cohort 1966, with clinical examinations at ages 31 and 46. The sample included self-reported PCOS (age 31, n = 190; age 46, n = 207) and referent women (age 31, n = 1054; age 46, n = 1324) with data on LTL.

METHODS

The association between LTL and PCOS at ages 31 and 46 was analyzed by linear regression models adjusted for BMI, smoking, alcohol consumption and socioeconomic status at the corresponding age.

RESULTS

Women with PCOS had similar mean LTL at ages 31 and 46 (P > 0.4 for both). The mean LTL change between ages 31 and 46 did not differ between groups (P = 0.19). However, we observed a significant LTL attrition between ages 31 and 46 in the reference population (P < 0.001), but not in women with PCOS (P = 0.96).

CONCLUSIONS

This finding may suggest a difference in the LTL attrition rate in women with PCOS, an unexpected finding that might affect their risk of age-related disease. Further research is needed to clarify the underlying mechanisms.

Critical evaluation of deep neural networks for wrist fracture detection

Wrist Fracture is the most common type of fracture with a high incidence rate. Conventional radiography (i.e. X-ray imaging) is used for wrist fracture detection routinely, but occasionally fracture delineation poses issues and an additional confirmation by computed tomography (CT) is needed for diagnosis. Recent advances in the field of Deep Learning (DL), a subfield of Artificial Intelligence (AI), have shown that wrist fracture detection can be automated using Convolutional Neural Networks. However, previous studies did not pay close attention to the difficult cases which can only be confirmed via CT imaging. In this study, we have developed and analyzed a state-of-the-art DL-based pipeline for wrist (distal radius) fracture detection-DeepWrist, and evaluated it against one general population test set, and one challenging test set comprising only cases requiring confirmation by CT. Our results reveal that a typical state-of-the-art approach, such as DeepWrist, while having a near-perfect performance on the general independent test set, has a substantially lower performance on the challenging test set-average precision of 0.99 (0.99-0.99) versus 0.64 (0.46-0.83), respectively. Similarly, the area under the ROC curve was of 0.99 (0.98-0.99) versus 0.84 (0.72-0.93), respectively. Our findings highlight the importance of a meticulous analysis of DL-based models before clinical use, and unearth the need for more challenging settings for testing medical AI systems.

Androgen Profile Through Life in Women With Polycystic Ovary Syndrome: A Nordic Multicenter Collaboration Study

CONTEXT

Women with polycystic ovary syndrome (PCOS) have increased androgen secretion throughout fertile life; however, the data on the effect of menopause on hyperandrogenemia in these women are scarce. Nevertheless, large comprehensive comparative studies on age-related androgen levels in women with PCOS are lacking.

OBJECTIVE

The objective of the study was to investigate the effect of age on serum androgen levels in women with PCOS and to determine cutoff values for androgens and SHBG associated with a PCOS diagnosis.

DESIGN

This was a case-control study.

SETTING

The study was conducted in five university sites in the Nordic countries.

PATIENTS

In all, 681 women with PCOS and 230 referent women were grouped according to age into seven age groups (18 to > 50 y).

INTERVENTIONS

There were no interventions.

MAIN OUTCOME MEASURES

T, SHBG, free androgen index (FAI), calculated free T (cFT), androstenedione (A4), and dehydroepiandrosterone sulfate were measured.

RESULTS

Androgen levels in women with PCOS decreased with age toward menopause. The difference between women with PCOS and the referent women narrowed and individual variation increased as they approached menopause. T levels, FAI, and cFT were significantly higher in women with PCOS aged 18-44 years (P < .001, adjusted for body mass index). The best predictive factors for having PCOS were cFT (≥0.40 ng/dL, odds ratio [OR] 7.90), FAI (≥2.0, OR 6.71), and A4 (≥277.94 ng/dL, OR 6.16).

CONCLUSIONS

Women with PCOS had elevated serum androgen levels also after menopause. The parameters that best predicted PCOS at all ages were cFT, A4, and FAI.

Anti-Müllerian hormone: correlation with testosterone and oligo- or amenorrhoea in female adolescence in a population-based cohort study

STUDY QUESTIONS

Can serum anti-Müllerian hormone (AMH) levels measured in female adolescents predict polycystic ovary syndrome (PCOS)-associated features in adolescence and early adulthood?

SUMMARY ANSWER

AMH levels associated well with PCOS-associated features (such as testosterone levels and oligoamenorrhoea) in adolescence, but was not an ideal marker to predict PCOS-associated features in early adulthood.

WHAT IS KNOWN ALREADY

Several studies have reported that there is a strong correlation between antral follicle count and serum AMH levels and that women with PCOS/PCO have significantly higher serum AMH levels than women with normal ovaries. Other studies have reported an association between AMH serum levels and hyperandrogenism in adolescence, but none has prospectively assessed AMH as a risk predictor for developing features of PCOS during adulthood.

STUDY DESIGN, SIZE, DURATION

A subset of 400 girls was selected from the prospective population-based Northern Finland Birth Cohort 1986 (n = 4567 at age 16 and n = 4503 at age 26). The population has been followed from 1986 to the present.

PARTICIPANTS/MATERIAL, SETTING, METHODS

At age 16, 400 girls (100 from each testosterone quartile: 50 with oligo- or amenorrhoea and 50 with a normal menstrual cycle) were selected at random from the cohort for AMH measurement. Metabolic parameters were also assessed at age 16 in all participants. Postal questionnaires enquired about oligo- or amenorrhoea, hirsutism, contraceptive use and reproductive health at ages 16 and 26.

MAIN RESULTS AND ROLE OF CHANCE

There was a significant correlation between AMH and testosterone at age 16 (r = 0.36, P < 0.001). AMH levels at age 16 were significantly higher among girls with oligo- or amenorrhoea compared with girls with normal menstrual cycles (35.9 pmol/l [95% CI: 33.2;38.6] versus 27.7 pmol/l [95% CI: 25.0;30.4], P < 0.001). AMH at age 16 was higher in girls who developed hirsutism at age 26 compared with the non-hirsute group (31.4 pmol/l [95% CI 27.1;36.5] versus 25.8 pmol/l [95% CI 23.3;28.6], P = 0.036). AMH at age 16 was also higher in women with PCOS at age 26 compared with the non-PCOS subjects (38.1 pmol/l [95% CI 29.1;48.4] versus 30.2 pmol/l [95% CI 27.9;32.4], P = 0.044). The sensitivity and specificity of the AMH (cut-off 22.5 pmol/l) for predicting PCOS at age 26 was 85.7 and 37.5%, respectively. The addition of testosterone did not significantly improve the accuracy of the test. There was no significant correlation between AMH levels and metabolic indices at age 16.

IMPLICATIONS, REASONS FOR CAUTION

AMH is related to oligo- or amenorrhoea in adolescence, but it is not a good marker for metabolic factors. The relatively low rate of participation in the questionnaire at age 26 may also have affected the results. AMH was measured in a subset of the whole cohort. AMH measurement is lacking international standardization and therefore the concentrations and cut-off points are method dependent.

WIDER IMPLICATIONS FOR THE FINDINGS

Using a high enough cut-off value of AMH to predict which adolescents are likely to develop PCOS in adulthood could help to manage the condition from an early age due to a good sensitivity. However, because of its low specificity, it is not an ideal diagnostic marker, and its routine use in clinical practice cannot, at present, be recommended.

STUDY FUNDINGS AND COMPETING INTERESTS

The study was funded by a grant from Wellcome Trust (089549/Z/09/Z) to H.L., S.F. and M.-R.J. Study funding was also received from Oulu University Hospital Research Funds, Sigrid Juselius Foundation and the Academy of Finland. None of the authors have any competing interest to declare.

Menstrual disorders in adolescence: a marker for hyperandrogenaemia and increased metabolic risks in later life? Finnish general population-based birth cohort study

STUDY QUESTION

Are self-reported menstrual disorders associated with hyperandrogenaemia and metabolic disturbances as early as in adolescence?

SUMMARY ANSWER

Menstrual disorders at the age 16 are a good marker of hyperandrogenaemia, and an adverse lipid profile was associated with higher androgen levels.

WHAT IS KNOWN AND WHAT THIS PAPER ADDS

Hyperandrogenism per se has been suggested to be a significant metabolic risk factor in women and a cause of physical and psychological morbidity in adolescent girls. A weak positive correlation has been described between hyperandrogenaemia and obesity in adolescent girls, but the clinical consequences are still poorly understood. Hyperandrogenism and insulin resistance are also key features of polycystic ovary syndrome (PCOS), and women with PCOS are consequently at an increased risk of developing type 2 diabetes mellitus and/or metabolic syndrome, and may have increased cardiovascular morbidity. Our findings confirm that the association between menstrual disorders, hyperandrogenism, obesity and metabolic risks is already evident in adolescence.

STUDY DESIGN

This population-based, cross-sectional study used postal questionnaires to targeting 15-16-year-old girls in the Northern Finland Birth Cohort 1986 (n= 4567).

PARTICIPANTS AND SETTING

There were 3669 girls who answered the postal questionnaire and out of 3373 girls who also underwent clinical examinations and blood tests, 2448 were included in the analyses. The questionnaire included one question about the regularity and length of the menstrual cycle: 'Is your menstrual cycle (the interval from the beginning of one menstrual period to the beginning of the next period) often (more than twice a year) longer than 35 days?' The girls who answered 'yes' to this question were considered to be suffering from menstrual disorders and were classified as 'symptomatic'. The girls who answered 'no' were defined as 'non-symptomatic'.

MAIN RESULTS AND THE ROLE OF CHANCE

There were 709 (29%) girls who reported menstrual disorders (symptomatic girls) and 1739 who had regular periods (non-symptomatic girls). In the whole population and in both study groups, there were significant correlations between body mass index (BMI) (and waist-to-hip ratio), hyperandrogenaemia and metabolic parameters. Symptomatic girls exhibited significantly higher serum concentrations of testosterone (P= 0.010), lower levels of sex hormone-binding globulin (P =0.042) and higher free androgen indices [FAIs; geometric mean 3.38 (interquartile range (IQR): 2.27, 5.18) versus 3.08 (IQR: 2.15, 4.74), P= 0.002]. The two groups had comparable BMI and insulin sensitivity, and serum levels of glucose, insulin and lipids. There was a significant linear trend towards higher FAI values in the higher BMI quartiles in both symptomatic and non-symptomatic girls. In the whole population, there was a statistically significant linear decrease in high-density lipoprotein concentrations (P < 0.001) and higher triglyceride concentrations (P =0.004) in the upper FAI quartile.

IMPLICATIONS

Information regarding menstrual disorders in adolescence is a good marker of hyperandrogenaemia and may be an early risk factor for the development of PCOS in adulthood. The association between obesity, hyperandrogenism and metabolic risks is already evident in adolescence, which strengthens the importance of noting menstrual disorders at an early stage. BIAS, LIMITATIONS, GENERALIZABILITY: The cross-sectional nature of the study does not allow us to draw conclusions concerning the metabolic risks of this population in later life. The diagnosis of menstrual disorders was based on a questionnaire, suggesting a risk of information bias in reporting the symptoms. This study was not designed to diagnose PCOS, as ultrasonography was not available and there was no clinical evaluation of hyperandrogenism (i.e. hirsutism). However, we were able to take into account potential confounding factors in the analyses.

STUDY FUNDING/COMPETING INTERESTS

This work was supported by grants from the Finnish Medical Society Duodecim, the North Ostrobothnia Regional Fund, the Academy of Finland (project grants 104781, 120315, 129269, 1114194, SALVE), University Hospital Oulu, Biocenter, University of Oulu, Finland (75617), the European Commission (EURO-BLCS, Framework 5 award QLG1-CT-2000-01643) and the Medical Research Council, UK (PrevMetSyn/SALVE). None of the authors have any conflict of interest to declare.