RESUMEN
The co-occurrence of insulin resistance (IR)-related metabolic conditions with neuropsychiatric disorders is a complex public health challenge. Evidence of the genetic links between these phenotypes is emerging, but little is currently known about the genomic regions and biological functions that are involved. To address this, we performed Local Analysis of [co]Variant Association (LAVA) using large-scale (N=9,725-933,970) genome-wide association studies (GWASs) results for three IR-related conditions (type 2 diabetes mellitus, obesity, and metabolic syndrome) and nine neuropsychiatric disorders. Subsequently, positional and expression quantitative trait locus (eQTL)-based gene mapping and downstream functional genomic analyses were performed on the significant loci. Patterns of negative and positive local genetic correlations (|rg|=0.21-1, pFDR<0.05) were identified at 109 unique genomic regions across all phenotype pairs. Local correlations emerged even in the absence of global genetic correlations between IR-related conditions and Alzheimer's disease, bipolar disorder, and Tourette's syndrome. Genes mapped to the correlated regions showed enrichment in biological pathways integral to immune-inflammatory function, vesicle trafficking, insulin signalling, oxygen transport, and lipid metabolism. Colocalisation analyses further prioritised 10 genetically correlated regions for likely harbouring shared causal variants, displaying high deleterious or regulatory potential. These variants were found within or in close proximity to genes, such as SLC39A8 and HLA-DRB1, that can be targeted by supplements and already known drugs, including omega-3/6 fatty acids, immunomodulatory, antihypertensive, and cholesterol-lowering drugs. Overall, our findings underscore the complex genetic landscape of IR-neuropsychiatric multimorbidity, advocating for an integrated disease model and offering novel insights for research and treatment strategies in this domain.
RESUMEN
OBJECTIVES: Distinguishing sporadic behavioral variant of frontotemporal dementia (bvFTD) from late-onset primary psychiatric disorders (PPD) remains challenging with the lack of robust biomarkers. An early bvFTD misdiagnosis in PPD cases and vice-versa is common. Little is known about diagnostic (in)stability over longer period of time. We investigated diagnostic instability in a neuropsychiatric cohort up to 8 years after baseline visit and identified which clinical hallmarks contribute to diagnostic instability. DESIGN: Diagnoses of participants of the late-onset frontal lobe (LOF) study were collected from the baseline visit (T0) and the 2-year follow-up visit (T2). Clinical outcomes were retrieved 5-8 years after baseline visit (Tfinal). Endpoint diagnoses were categorized into bvFTD, PPD and other neurological disorders (OND). We calculated the total amount of participants that switched diagnosis between T0-T2 and T2-Tfinal. Clinical records of participants that switched diagnosis were assessed. RESULTS: Of the 137 patients that were included in the study, the final diagnoses at Tfinal were bvFTD 24.1% (n = 33), PPD 39.4% (n = 54), OND 33.6% (n = 46) and unknown 2.9% (n = 4). Between T0 and T2, a total of 29 (21.2%) patients switched diagnosis. Between T2 and Tfinal, 8 (5.8%) patients switched diagnosis. Prolonged follow-up identified few cases with diagnostic instability. Major contributors to diagnostic instability where a nonconverting diagnosis of possible bvFTD and a probable bvFTD diagnosis based on informant-based history and an abnormal FDG-PET scan whilst having a normal MRI. CONCLUSION: Considering these lessons, a FTD diagnosis remains stable enough to conclude that 2 years is sufficient to say if a patient with late-life behavioral disorder has FTD.
