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The Most Important, Unknown Gene in Human Reproduction and Beyond: the FMR1 Gene

The Most Important, Unknown Gene in Human Reproduction and Beyond: the FMR1 Gene. Norbert Gleicher, MD Medical Director, Center for Human Reproduction – New York President, Foundation for Reproductive Medicine. Grandrounds , Center for Human Reproduction, New York, NY – June 12, 2012.

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The Most Important, Unknown Gene in Human Reproduction and Beyond: the FMR1 Gene

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  1. The Most Important, Unknown Gene in Human Reproduction and Beyond: the FMR1 Gene Norbert Gleicher, MD Medical Director, Center for Human Reproduction – New York President, Foundation for Reproductive Medicine Grandrounds, Center for Human Reproduction, New York, NY – June 12, 2012

  2. Conflict Statement • Dr. Gleicher is listed as co-inventor on a number of pending patent applications claiming diagnostic and therapeutic benefits from determination of CGG repeat numbers and ovarian FMR1 genotypes and sub-genotypes.

  3. The FMR1 gene is located on the long (q) arm of the X chromosome at position 27.3. More precisely, the FMR1 gene is located from base pair 146,993,468 to base pair 147,032,646 on the X chromosome.

  4. Premature Ovarian Senescence *Nikolaou and Templeton, Hum Reprod 2003

  5. Premature ovarian senescence has (at least) 2 specific geno-/phenotypes: Genetic Autoimmunity ≥31 CGG Repeats No Autoimmunity Severe Ovarian Dysfunction Higher FSH Lower AMH <30 CGG Repeats Autoimmunity Milder Ovarian Dysfunction Lower FSH Higher AMH Gleicher et al. FertilSteril2009;5:1707-11.

  6. The General population distribution (solid Gray) is based on Fu et al (Fu et al., 1991), while the distribution in an infertile population (allele 1 ; allele-2 ) is based on Gleicher et al (Gleicher et al., 2008). Group A is the low range (≤ 28 repeats in allele-1); Group B represents the ”normal” range (>28 in allele-1 and < 34 repeats in allele-2); and Group C is representative of the high range (≥ 34 repeats in allele-2). Fu’s distribution is representative of an average population, while Gleicher’s distribution curve, demonstrating a right-shift from Fu’s curve, investigated an infertile population with considerable prevalence of diminished ovarian reserve (Gleicher et al., 2008). Gleicher et al. Reprod Biomed Online 2009; 19:385-90.

  7. Logistic Regressions in Groups A and C The figure represents logistic regressions, demonstrating predicted relative risk (RR) of having AMH of less than 0.8 ng/ml over CGG repeat counts, stratified by age. Blue dots (and blue line) represent women ≥ 38 years of age; Red dots (and green line) represent age < 38 years. The black line reflects women of all ages. RR of diminished ovarian reserve, as reflected by AMH, progressively increases in the presence of CGG counts below and above 30 repeats. For every 5 repeat decrease in CGG count below 30, the relative risk of low AMH increases by 60%. For every 5 repeat increase in CGG repeat count above 30 the relative risk of low AMH is increased by 40%. Gleicher et al. Reprod Biomed Online 2009; 19:385-90.

  8. Triple CGG counts by box and whisker plotfor entire patient population Gleicher et al. Reprod Biomed Online; In Press.

  9. Triple CGG counts by box and whisker plots for individual racial/ethnic groups Gleicher et al. Reprod Biomed Online; In Press.

  10. Linear regression of association between AMH levels and age based on FMR1 status The figure represents egg donors and infertility patients at all ages. Normal females at young ages have the highest, and women with homozygous CGG count abnormalities the lowest AMH levels. AMH levels, however, decline in normal women more rapidly than in heterozygous and homozygous patients. At approximately 35 years of age AMH levels in heterozygous women start to exceed those of normal women. AMH levels in homozygous women track those of normal women almost till age 50, when they start exceeding the latter. Gleicher et al. Reprod Biomed Online; In Press.

  11. Distribution of FMR1 genotypes and sub-genotypes in oocyte donors Gleicher et al, JARG 2012, in press

  12. het-norm/low is associated with: • PCOS-like ovarian phenotype • Rapidly depleting ovarian reserve • Non-hyperandrogenic • Non-obese • Autoimmunity • Low IVF pregnancy chances Gleicher et al. PLoS One 2010;5(12):e15303.

  13. Relevance of autoimmunity in reference to FMR1 genotype The prevalence of autoimmunity was in both patient groups the highest with het-norm/low FMR1 genotype and the lowest with het-norm/high genotype. This pattern, however, intensified in women with PCO-like phenotype. Gray bars represent women with normal ovarian reserve; white bars represent the PCO-like phenotype. Gleicher et al. PLoS One 2010;5(12):e15303.

  14. X chromosome contains the largest number of immune-related genes of the whole human genome. Bianchi et al., J Autoimmune 2012;38:J187-92.

  15. Pregnancy rates in IVF based on FMR1 genotype Pregnancy rates were highest with normFMR1 genotype and the lowest with het-norm/low genotype. Gleicher et al. PLoS One 2010;5(12):e15303.

  16. Gleicher et al, PLoS One 2011;6(4):e18781

  17. Prevalence of autoimmunity based on race/ethnicity and FMR1 genotype Autoimmunity, overall, did not differ amongst the three races/ethnicities. Panel A, however, demonstrates differences in prevalence of autoimmunity within races, while Panel B demonstrates the same data stratified by FMR1 genotype. The interaction between race/ethnicity and FMR1 genotypes, overall, almost reached significance (P = 0.07), suggesting different FMR1 effects in the three races/ethnicities. Logistic regression, with race/ethnicity and interaction between FMR1 genotype and autoimmunity in the model, has 2.5-times the odds of being associated with autoimmune positivity (OR 2.5, 1.34–4.55; P = 0.004). Gleicher et al, PLoS One 2011;6(4):e18781

  18. Gleicher et al, submitted for publication.

  19. Distribution of FMR1 genotypes and sub-genotypes in women with BRCA1/2 mutations (black bars) and U.S. (gray) comparison group; * within each category denotes significance at P<0.05. Noteworthy are the excess of het-norm/low and complete absence of het-norm/high in FMR1 sub-genotypes in BRCA1/2 mutation carriers, and the very low prevalence of women with normFMR1 genotype. A numerical presentation of these data is presented in (a), In description of genotypes norm stands for normal, het for heterozygous and hom for homozygous. In description of sub-genotypes high stands for CGG n>34 and low for CGG n<26. Gleicher et al, submitted for publication.

  20. Distribution on both FMR1 alleles, of CGG n in BRCA1/2 mutation carriers as well as U.S. controls in form of scattergrams. Horizontal and vertical parallel lines in scattergrams define the norm distribution area (CGG n=26-34), with areas below and above representing low and high, sub-genotypes, respectively; a represents higher and lower count allele, respectively, for individual patients. Only the lower count allele varied significantly between the two groups (Mann-Whitney U test, P<0.001). Scattergrams, as well as a, demonstrate graphically the significant shift towards lowFMR1 sub-genotypes, especially on the lower count allele of BRCA1/2 mutation carriers. In a - - - represents mean; ______ represents median. Gleicher et al, submitted for publication.

  21. Androgen conversion rates by age and FMR1 genotypes and sub-genotypes Two-way ANOVA for pregnancy outcome and age group demonstrated significant interaction (P=0.025). A: There was also a significant interaction between pregnant and non-pregnant women (P=0.015), independently observed in younger women only (P=0.007). Amongst pregnant women, older women also demonstrated a significantly lower androgen conversion rate from DHEA to T (P<0.001). B demonstrates that androgen conversion rates differ significantly between FMR1 genotypes and sub-genotypes (P=0.021), between younger and older patients (P=0.003), and in the interaction term between FMR1 and age (P=0.057). *Post-hoc comparison (Holm-Sidack) demonstrated that sub-genotype het-norm/high converts androgens significantly more efficiently than het-norm/low.(P=0.003), and younger convert androgens more efficiently than older women (P=0.003).

  22. FMR1 genotypes and sub-genotypes stratified by age A A demonstrates that in women ≤ 38 years Δ TTBL to TTCSFMR1 genotypes and sub-genotypes, overall significantly changed (P=0.024). Post-hoc comparisons further demonstrated that this change in Δ of mean TT was significantly smaller for het-norm/low than het-norm/high (P= 0.028) or norm (P=0.009) but mean ratio values between androgens did not differ. As B demonstrates, older women > age 38 behaved differently: DHEASCS differed significantly between FMR1 genotypes and sub-genotypes (P=0.026), and post-hoc analysis confirmed that DHEASCS was significantly higher in hom than het-norm/high (P=0.003) and het-norm/low women (P=0.005). Older women, however, also demonstrated significant differences in mean androgen ratios: C demonstrates that DHEASCS/DHEACS differed significantly between FMR1 genotypes and sub-genotypes (P=0.024), and post-hoc analysis suggested that hom women had a significantly higher ratio than het-norm/high (P=0.003), het-norm/low (P=0.005) and norm women (P=0.013). B C

  23. Evolution of the gene • “Ur-Gene”: • Mutations: Promoter region 26-35 CGGs Expansion > 34 CGGs → Neuro/psych risks Constriction < 26 CGGs → Autoimmunity → BRCA 1/2 cancers

  24. PRINCIPAL COLLABORATORS: David H Barad, MD, MS, CHR Andrea Weghofer, MD, PhD, MBA, MS, Medical University Vienna Ho-Joon Lee, PhD, CHR Tamar Michaeli, PhD, CHR Aya Shohat-Tal, PhD, CHR Ann Kim, MA, Statistician, CHR

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