Characterization of the genetic landscape of Alzheimer’s disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/‘proxy’ AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele.

Genetic discoveries of Alzheimer’s disease are the drivers of our understanding, and together with polygenetic risk stratification can contribute towards planning of feasible and efficient preventive and curative clinical trials. We first perform a large genetic association study by merging all available case-control datasets and by-proxy study results (discovery n = 409,435 and validation size n = 58,190). Here, we add six variants associated with Alzheimer’s disease risk (near APP, CHRNE, PRKD3/NDUFAF7, PLCG2 and two exonic variants in the SHARPIN gene). Assessment of the polygenic risk score and stratifying by APOE reveal a 4 to 5.5 years difference in median age at onset of Alzheimer’s disease patients in APOE ɛ4 carriers. Because of this study, the underlying mechanisms of APP can be studied to refine the amyloid cascade and the polygenic risk score provides a tool to select individuals at high risk of Alzheimer’s disease.

Fibromyalgia is a complex, relatively unknown disease characterised by chronic, widespread musculoskeletal pain. The gut-brain axis connects the gut microbiome with the brain through the enteric nervous system (ENS); its disruption has been associated with psychiatric and gastrointestinal disorders. To gain an insight into the pathogenesis of fibromyalgia and identify diagnostic biomarkers, we combined different omics techniques to analyse microbiome and serum composition. We collected faeces and blood samples to study the microbiome, the serum metabolome and circulating cytokines and miRNAs from a cohort of 105 fibromyalgia patients and 54 age- and environment-matched healthy individuals. We sequenced the V3 and V4 regions of the 16S rDNA gene from faeces samples. UPLC-MS metabolomics and custom multiplex cytokine and miRNA analysis (FirePlex™ technology) were used to examine sera samples. Finally, we combined the different data types to search for potential biomarkers. We found that the diversity of bacteria is reduced in fibromyalgia patients. The abundance of the Bifidobacterium and Eubacterium genera (bacteria participating in the metabolism of neurotransmitters in the host) in these patients was significantly reduced. The serum metabolome analysis revealed altered levels of glutamate and serine, suggesting changes in neurotransmitter metabolism. The combined serum metabolomics and gut microbiome datasets showed a certain degree of correlation, reflecting the effect of the microbiome on metabolic activity. We also examined the microbiome and serum metabolites, cytokines and miRNAs as potential sources of molecular biomarkers of fibromyalgia. Our results show that the microbiome analysis provides more significant biomarkers than the other techniques employed in the work. Gut microbiome analysis combined with serum metabolomics can shed new light onto the pathogenesis of fibromyalgia. We provide a list of bacteria whose abundance changes in this disease and propose several molecules as potential biomarkers that can be used to evaluate the current diagnostic criteria.

Mutations in the LRRK2 kinase are the most common cause of familial Parkinson’s disease, and variants increase risk for the sporadic form of the disease. LRRK2 phosphorylates multiple RAB GTPases including RAB8A and RAB10. Phosphorylated RAB10 is recruited to centrosome-localized RILPL1, which may interfere with ciliogenesis in a disease-relevant context. Our previous studies indicate that the centrosomal accumulation of phosphorylated RAB8A causes centrosomal cohesion deficits in dividing cells, including in peripheral patient-derived cells. Here, we show that both RAB8 and RAB10 contribute to the centrosomal cohesion deficits. Pathogenic LRRK2 causes the centrosomal accumulation not only of phosho-RAB8 but also of phospho-RAB10, and the effects on centrosomal cohesion are dependent on RAB8, RAB10 and RILPL1. Conversely, the pathogenic LRRK2-mediated ciliogenesis defects correlate with the centrosomal accumulation of both phospho-RAB8 and phospho-RAB10. LRRK2-mediated centrosomal cohesion and ciliogenesis alterations are observed in patient-derived peripheral cells, as well as in primary astrocytes from mutant LRRK2 mice, and are reverted upon LRRK2 kinase inhibition. These data suggest that the LRRK2-mediated centrosomal cohesion and ciliogenesis defects are distinct cellular readouts of the same underlying phospho-RAB8/RAB10/RILPL1 nexus and highlight the possibility that either centrosomal cohesion and/or ciliogenesis alterations may serve as cellular biomarkers for LRRK2-related PD.

Kynurenic acid (KYNA) is a product of the tryptophan (TRP) metabolism via the kynurenine pathway (KP). This pathway is activated in neurodegenerative disorders, such as Alzheimer´s disease (AD). KYNA is primarily produced by astrocytes and is considered neuroprotective. Thus, altered KYNA levels may suggest an inflammatory response. Very recently, significant increases in KYNA levels were reported in cerebrospinal fluid (CSF) from AD patients compared with normal controls. In this study, we assessed the accuracy of KYNA in CSF for the classification of patients with AD, cognitively healthy controls, and patients with a variety of other neurodegenerative diseases, including frontotemporal dementia (FTD), amyotrophic lateral sclerosis (ALS), and progressive supranuclear palsy (PSP). Averaged KYNA concentration in CSF was higher in patients with AD when compared with healthy subjects and with all the other differentially diagnosed groups. There were no significant differences in KYNA levels in CSF between any other neurodegenerative groups and controls. These results suggest a specific increase in KYNA concentration in CSF from AD patients not seen in other neurodegenerative diseases.

The term neuromuscular disorder (NMD) includes many genetic and acquired diseases and differential diagnosis can be challenging. Next-generation sequencing (NGS) is especially useful in this setting given the large number of possible candidate genes, the clinical, pathological, and genetic heterogeneity, the absence of an established genotype-phenotype correlation, and the exceptionally large size of some causative genes such as TTN, NEB and RYR1. We evaluated the diagnostic value of a custom targeted next-generation sequencing gene panel to study the mutational spectrum of a subset of NMD patients in Spain. In an NMD cohort of 207 patients with congenital myopathies, distal myopathies, congenital and adult-onset muscular dystrophies, and congenital myasthenic syndromes, we detected causative mutations in 102 patients (49.3%), involving 42 NMD-related genes. The most common causative genes, TTN and RYR1, accounted for almost 30% of cases. Thirty-two of the 207 patients (15.4%) carried variants of uncertain significance or had an unidentified second mutation to explain the genetic cause of the disease. In the remaining 73 patients (35.3%), no candidate variant was identified. In combination with patients’ clinical and myopathological data, the custom gene panel designed in our lab proved to be a powerful tool to diagnose patients with myopathies, muscular dystrophies and congenital myasthenic syndromes. Targeted NGS approaches enable a rapid and cost-effective analysis of NMD- related genes, offering reliable results in a short time and relegating invasive techniques to a second tier.