Unequal allelic expression of wild-type and mutated β-myosin in familial hypertrophic cardiomyopathy

Familial hypertrophic cardiomyopathy (FHC) is an autosomal dominant disease, which in about 30% of the patients is caused by missense mutations in one allele of the β-myosin heavy chain (β-MHC) gene (MYH7). To address potential molecular mechanisms underlying the family-specific prognosis, we determined the relative expression of mutant versus wild-type MYH7-mRNA. We found a hitherto unknown mutation-dependent unequal expression of mutant to wild-type MYH7-mRNA, which is paralleled by similar unequal expression of β-MHC at the protein level. Relative abundance of mutated versus wild-type MYH7-mRNA was determined by a specific restriction digest approach and by real-time PCR (RT-qPCR). Fourteen samples from M. soleus and myocardium of 12 genotyped and clinically well-characterized FHC patients were analyzed. The fraction of mutated MYH7-mRNA in five patients with mutation R723G averaged to 66 and 68% of total MYH7-mRNA in soleus and myocardium, respectively. For mutations I736T, R719W and V606M, fractions of mutated MYH7-mRNA in M. soleus were 39, 57 and 29%, respectively. For all mutations, unequal abundance was similar at the protein level. Importantly, fractions of mutated transcripts were comparable among siblings, in younger relatives and unrelated carriers of the same mutation. Hence, the extent of unequal expression of mutated versus wild-type transcript and protein is characteristic for each mutation, implying cis-acting regulatory mechanisms. Bioinformatics suggest mRNA stability or splicing effectors to be affected by certain mutations. Intriguingly, we observed a correlation between disease expression and fraction of mutated mRNA and protein. This strongly suggests that mutation-specific allelic imbalance represents a new pathogenic factor for FHC

Replication of Previous Findings? Comparing Gray Matter Volumes in Transgender Individuals with Gender Incongruence and Cisgender Individuals

The brain structural changes related to gender incongruence (GI) are still poorly understood. Previous studies comparing gray matter volumes (GMV) between cisgender and transgender individuals with GI revealed conflicting results. Leveraging a comprehensive sample of transmen (n = 33), transwomen (n = 33), cismen (n = 24), and ciswomen (n = 25), we employ a region-of-interest (ROI) approach to examine the most frequently reported brain regions showing GMV differences between trans- and cisgender individuals. The primary aim is to replicate previous findings and identify anatomical regions which differ between transgender individuals with GI and cisgender individuals. On the basis of a comprehensive literature search, we selected a set of ROIs (thalamus, putamen, cerebellum, angular gyrus, precentral gyrus) for which differences between cis- and transgender groups have been previously observed. The putamen was the only region showing significant GMV differences between cis- and transgender, across previous studies and the present study. We observed increased GMV in the putamen for transwomen compared to both transmen and ciswomen and for all transgender participants compared to all cisgender participants. Such a pattern of neuroanatomical differences corroborates the large majority of previous studies. This potential replication of previous findings and the known involvement of the putamen in cognitive processes related to body representations and the creation of the own body image indicate the relevance of this region for GI and its potential as a structural biomarker for G

Predictive Pattern Classification Can Distinguish Gender Identity Subtypes from Behavior and Brain Imaging

The exact neurobiological underpinnings of gender identity (i.e., the subjective perception of oneself belonging to a certain gender) still remain unknown. Combining both resting-state functional connectivity and behavioral data, we examined gender identity in cisgender and transgender persons using a data-driven machine learning strategy. Intrinsic functional connectivity and questionnaire data were obtained from cisgender (men/women) and transgender (trans men/trans women) individuals. Machine learning algorithms reliably detected gender identity with high prediction accuracy in each of the four groups based on connectivity signatures alone. The four normative gender groups were classified with accuracies ranging from 48% to 62% (exceeding chance level at 25%). These connectivity-based classification accuracies exceeded those obtained from a widely established behavioral instrument for gender identity. Using canonical correlation analyses, functional brain measurements and questionnaire data were then integrated to delineate nine canonical vectors (i.e., brain-gender axes), providing a multilevel window into the conventional sex dichotomy. Our dimensional gender perspective captures four distinguishable brain phenotypes for gender identity, advocating a biologically grounded reconceptualization of gender dimorphism. We hope to pave the way towards objective, data-driven diagnostic markers for gender identity and transgender, taking into account neurobiological and behavioral differences in an integrative modeling approach

More than Just Two Sexes : the Neural Correlates of Voice Gender Perception in Gender Dysphoria

Gender dysphoria (also known as "transsexualism") is characterized as a discrepancy between anatomical sex and gender identity. Research points towards neurobiological influences. Due to the sexually dimorphic characteristics of the human voice, voice gender perception provides a biologically relevant function, e.g. in the context of mating selection. There is evidence for a better recognition of voices of the opposite sex and a differentiation of the sexes in its underlying functional cerebral correlates, namely the prefrontal and middle temporal areas. This fMRI study investigated the neural correlates of voice gender perception in 32 male-to-female gender dysphoric individuals (MtFs) compared to 20 non-gender dysphoric men and 19 non-gender dysphoric women. Participants indicated the sex of 240 voice stimuli modified in semitone steps in the direction to the other gender. Compared to men and women, MtFs showed differences in a neural network including the medial prefrontal gyrus, the insula, and the precuneus when responding to male vs. female voices. With increased voice morphing men recruited more prefrontal areas compared to women and MtFs, while MtFs revealed a pattern more similar to women. On a behavioral and neuronal level, our results support the feeling of MtFs reporting they cannot identify with their assigned sex

Data from: More than just two sexes: the neural correlates of voice gender perception in gender dysphoria

Gender dysphoria (also known as “transsexualism”) is characterized as a discrepancy between anatomical sex and gender identity. Research points towards neurobiological influences. Due to the sexually dimorphic characteristics of the human voice, voice gender perception provides a biologically relevant function, e.g. in the context of mating selection. There is evidence for a better recognition of voices of the opposite sex and a differentiation of the sexes in its underlying functional cerebral correlates, namely the prefrontal and middle temporal areas. This fMRI study investigated the neural correlates of voice gender perception in 32 male-to-female gender dysphoric individuals (MtFs) compared to 20 non-gender dysphoric men and 19 non-gender dysphoric women. Participants indicated the sex of 240 voice stimuli modified in semitone steps in the direction to the other gender. Compared to men and women, MtFs showed differences in a neural network including the medial prefrontal gyrus, the insula, and the precuneus when responding to male vs. female voices. With increased voice morphing men recruited more prefrontal areas compared to women and MtFs, while MtFs revealed a pattern more similar to women. On a behavioral and neuronal level, our results support the feeling of MtFs reporting they cannot identify with their assigned sex