Data-driven phenotype discovery of FMR1 premutation carriers in a population-based sample

Abstract

The impact of the FMR1 premutation on human health is the subject of considerable controversy. A fundamental unanswered question is whether carrying the premutation allele is directly correlated with clinical phenotypes. A challenging problem in past genotype-phenotype studies of the FMR1 premutation is ascertainment bias, which could lead to invalid research conclusions and negatively affect clinical practice. Here, we created the first population-based FMR1-informed biobank to find the pattern of health characteristics in premutation carriers. Our extensive phenotyping shows that premutation carriers experience a clinical profile that is significantly different from controls and is evident throughout adulthood. Comprehensive understanding of the clinical risk associated with this genetic variant is critical for premutation carriers, their families, and clinicians and has important implications for public health.

Characterization of the Metabolic, Clinical and Neuropsychological Phenotype of Female Carriers of the Premutation in the X-Linked FMR1 Gene

“…Mounting evidence has shown that female carriers of the PM are at higher risk for developing several health-related issues compared to non-carrier females (Bailey et al, 2008;Hunter et al, 2010;Winarni et al, 2012;Wheeler et al, 2014b;Movaghar et al, 2019). Awareness of these risks and correlation of the clinical signs with the biochemical footprint of carriers could help to identify critical biomarkers in early diagnosis and likely prognosis.…”

“…Women with alleles between 35-44 CGG repeats seem to present diminished ovarian function but regular menses and occult primary ovarian insufficiency (Streuli et al, 2009;Karimov et al, 2011;Pastore et al, 2012); however, other studies found no association between FMR1 intermediate alleles and POI (Bennett et al, 2010;Murray et al, 2014;Voorhuis et al, 2014). Other medical and psychological issues reported in females are hypothyroidism, hypertension, endocrine dysfunctions, chronic pain, fibromyalgia, autoimmune diseases, neuropathies, migraines, dementia, and psychiatric conditions, such as anxiety and depression (Allen et al, 2007(Allen et al, , 2020Bailey et al, 2008;Hunter et al, 2010;Winarni et al, 2012;Wheeler et al, 2014a,b;Lozano et al, 2016;Movaghar et al, 2019). Collectively included under the term FXAND [fragile Xassociated neuropsychiatric disorders; (Hagerman et al, 2018)], such emotional and neuropsychiatric disorders, have been shown to be more common in female carriers compared to noncarriers.…”

Autistic traits and mental health in women with the fragile-X premutation: maternal status versus genetic risk

“…21 Findings relating to mental health and parental stress were also consistent with previous literature. [5][6][7][8][9][10][11]17,18 Anxiety, depression and indicators of parental stress were significantly higher in all three groups of mothers of children with neurodevelopmental disorders relative to mothers of typically developing children. Mothers of children with Smith-Magenis syndrome were at particularly significant risk of experiencing severe depression relative to mothers of children with FXS or autistic children.…”

“…4 Recent literature strongly indicates that the FX-p is also a risk marker for autistic traits and negative mental health outcomes. [5][6][7][8][9][10][11] This risk is evident prior to having a child with FXS. 12,13 Although negative mental health outcomes are thought to be the most common challenges faced by individuals with the FX-p, 14 research to date has focused primarily on associated physical conditions.…”

SKiM - A generalized literature-based discovery system for uncovering novel biomedical knowledge from PubMed

“…Many existing LBD systems 10,20,21 and popular text mining systems such as PolySearch2 2 use a co-occurrence approach for extracting information from PubMed. KinderMiner gave interesting and promising results on identifying transcription factors for cell reprogramming, retrieved potential drugs for lowering blood glucose 19 , performed better than STRING 22 and PolySearch2 2 on retrieving mitochondrial protein-protein interactions (PPI) 23 , identified lab tests that can be repurposed for other diagnostic goals 24 , and identified phenotypes associated with FMR1 premutation 25 . In the current study, we applied SKiM on repurposing drugs for four diseases from the research articles published by Swanson and his colleagues 5,[26][27][28][29] : RD, migraine, Alzheimer's disease (AD), and schizophrenia.…”