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To accurately phenocopy human biology in vitro, researchers have been reducing their dependence on standard, static two-dimensional (2D) cultures and instead are moving towards three-dimensional (3D) and/or multicellular culture techniques. While these culture innovations are becoming more commonplace, there is a growing body of research that illustrates the benefits and even necessity of recapitulating the dynamic flow of nutrients, gas, waste exchange and tissue interactions that occur in vivo. However, cost and engineering complexity are two main factors that hinder the adoption of these technologies and incorporation into standard laboratory workflows. We developed LATTICE, a plug-and-play microfluidic platform able to house up to eight large tissue or organ models that can be cultured individually or in an interconnected fashion. The functionality of the platform to model both healthy and diseased tissue states was demonstrated using 3D cultures of reproductive tissues including murine ovarian tissues and human fallopian tube explants (hFTE). When exogenously exposed to pathological doses of gonadotropins and androgens to mimic the endocrinology of polycystic ovarian syndrome (PCOS), subsequent ovarian follicle development, hormone production and ovulation copied key features of this endocrinopathy. Further, hFTE cilia beating decreased significantly only when experiencing continuous media exchanges. We were then able to endogenously recreate this phenotype on the platform by dynamically co-culturing the PCOS ovary and hFTE. LATTICE was designed to be customizable with flexibility in 3D culture formats and can serve as a powerful automated tool to enable the study of tissue and cellular dynamics in health and disease in all fields of research. [ABSTRACT FROM AUTHOR]

Objective: Women with metabolic syndrome (MetS) have higher endogenous testosterone (T) levels than unaffected women. This study investigated whether hyperandrogenemia (HA) was a marker for increased cardiometabolic risk in reproductively normal premenopausal women.Methods: Reproductive hormones and metabolic parameters were assessed in 198 women with regular menses and no clinical hyperandrogenism (eumenorrheic [EM]). Hyperandrogenic EM women were compared with 110 women with NIH criteria polycystic ovary syndrome.Results: Twenty-two percent of EM women had HA. Levels of non-sex hormone-binding globulin (SHBG)-bound T were elevated in 68% of women, total T levels were elevated in 43% of women, and dehydroepiandrosterone sulfate levels were elevated in 30% of women. The prevalence of HA increased with BMI category (P = 0.01): 12% for BMI < 25 kg/m2 , 22% for BMI of 25 to 30 kg/m2 , and 31% for BMI ≥ 30 kg/m2 . MetS (adjusted odds ratio 2.9; 95% CI: 1.2-6.9) and dysglycemia risks (adjusted odds ratio 2.7; 95% CI: 1.2-5.8) were increased in hyperandrogenic EM women compared with normoandrogenic EM women, with adjustment for BMI. SHBG levels were independently associated with these metabolic end points (P < 0.001), whereas androgen levels were not. A cluster analysis confirmed that there was a discrete subset of EM women with HA and metabolic abnormalities.Conclusions: HA is common in EM women and is associated with increased risks for MetS and dysglycemia. However, low SHBG levels rather than elevated androgen levels may be the primary predictor of this relationship with metabolic dysfunction. [ABSTRACT FROM AUTHOR]

Polycystic ovary syndrome (PCOS) is a disorder characterized by hyperandrogenism, ovulatory dysfunction and polycystic ovarian morphology. Affected women frequently have metabolic disturbances including insulin resistance and dysregulation of glucose homeostasis. PCOS is diagnosed with two different sets of diagnostic criteria, resulting in a phenotypic spectrum of PCOS cases. The genetic similarities between cases diagnosed based on the two criteria have been largely unknown. Previous studies in Chinese and European subjects have identified 16 loci associated with risk of PCOS. We report a fixed-effect, inverse-weighted-variance meta-analysis from 10,074 PCOS cases and 103,164 controls of European ancestry and characterisation of PCOS related traits. We identified 3 novel loci (near PLGRKT, ZBTB16 and MAPRE1), and provide replication of 11 previously reported loci. Only one locus differed significantly in its association by diagnostic criteria; otherwise the genetic architecture was similar between PCOS diagnosed by self-report and PCOS diagnosed by NIH or non-NIH Rotterdam criteria across common variants at 13 loci. Identified variants were associated with hyperandrogenism, gonadotropin regulation and testosterone levels in affected women. Linkage disequilibrium score regression analysis revealed genetic correlations with obesity, fasting insulin, type 2 diabetes, lipid levels and coronary artery disease, indicating shared genetic architecture between metabolic traits and PCOS. Mendelian randomization analyses suggested variants associated with body mass index, fasting insulin, menopause timing, depression and male-pattern balding play a causal role in PCOS. The data thus demonstrate 3 novel loci associated with PCOS and similar genetic architecture for all diagnostic criteria. The data also provide the first genetic evidence for a male phenotype for PCOS and a causal link to depression, a previously hypothesized comorbid disease. Thus, the genetics provide a comprehensive view of PCOS that encompasses multiple diagnostic criteria, gender, reproductive potential and mental health. [ABSTRACT FROM AUTHOR]

Correction: Large-scale genome-wide meta-analysis of polycystic ovary syndrome suggests shared genetic architecture for different diagnosis criteria Table 2 The 14 genome-wide significant variants associated with PCOS in the meta-analysis. All PCOS meta-analysis, PCOS meta-analysis without self-report, NIH, non-NIH Rotterdam and self-report meta-analysis results. [Extracted from the article]

An amendment to this paper has been published and can be accessed via a link at the top of the paper. [ABSTRACT FROM AUTHOR]

Context: Polycystic ovary syndrome (PCOS) is a common, heritable endocrinopathy that is a common cause of anovulatory infertility in reproductive age women. Variants in LMNA cause partial lipodystrophy, a syndrome with overlapping features to PCOS., Objective: We tested the hypothesis that rare variation in LMNA contributes to PCOS pathogenesis and selects a lipodystrophy-like subtype of PCOS., Design, Setting, and Participants: We sequenced LMNA by targeted sequencing a discovery cohort of 811 PCOS patients and 164 healthy controls. We then analyzed LMNA from whole-exome sequencing (WES) of a replication cohort of 718 PCOS patients and 281 healthy controls., Main Outcome Measures: Variation in the LMNA gene, hormone and lipid profiles of participants., Results: In the discovery cohort, we identified 8 missense variants in 15/811 cases, and 1 variant in 1/172 reproductively healthy controls. There is strong evidence for association between the variants and PCOS compared to gnomAD non-Finnish European population controls (χ2=17, p=3.7x10-5, OR=2.9). In the replication cohort, we identified 11 unique variants in 15/718 cases, and 1 variant in 281 reproductively healthy controls. Again, there is strong evidence for association with population controls (χ2=30.5, p=3.4x10-8, OR= 4.0). In both the discovery and replication cohorts, variants in LMNA identify women with PCOS with high triglycerides and extreme insulin resistance., Conclusions: Rare missense variation in LMNA is reproducibly associated with PCOS and identifies some individuals with lipodystrophy-like features. The overlap between this PCOS phenotype and genetic partial lipodystrophy syndromes warrants further investigation into additional lipodystrophy genes and their potential in PCOS etiology., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Endocrine Society. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com. See the journal About page for additional terms.)