An Insertion Within SIRPß1 Shows a Dual Effect Over Alzheimer's Disease Cognitive Decline Altering the Microglial Response.

Background: Microglial dysfunction plays a causative role in Alzheimer's disease (AD) pathogenesis. Here we focus on a germline insertion/deletion variant mapping SIRPß1, a surface receptor that triggers amyloid-ß(Aß) phagocytosis via TYROBP. Objective: To analyze the impact of this copy-number variant in SIRPß1 expression and how it affects AD molecular etiology. Methods: Copy-number variant proxy rs2209313 was evaluated in GERALD and GR@ACE longitudinal series. Hippocampal specimens of genotyped AD patients were also examined. SIRPß1 isoform-specific phagocytosis assays were performed in HEK393T cells. Results: The insertion alters the SIRPß1 protein isoform landscape compromising its ability to bind oligomeric Aß and its affinity for TYROBP. SIRPß1 Dup/Dup patients with mild cognitive impairment show an increased cerebrospinal fluid t-Tau/Aß ratio (p = 0.018) and a higher risk to develop AD (OR = 1.678, p = 0.018). MRIs showed that Dup/Dup patients exhibited a worse initial response to AD. At the moment of diagnosis, all patients showed equivalent Mini-Mental State Examination scores. However, AD patients with the duplication had less hippocampal degeneration (p < 0.001) and fewer white matter hyperintensities. In contrast, longitudinal studies indicate that patients bearing the duplication allele show a slower cognitive decline (p = 0.013). Transcriptional analysis also shows that the SIRPß1 duplication allele correlates with higher TREM2 expression and an increased microglial activation. Conclusions: The SIRPß1 internal duplication has opposite effects over MCI-to-Dementia conversion risk and AD progression, affecting microglial response to Aß. Given the pharmacological approaches focused on the TREM2-TYROBP axis, we believe that SIRPß1 structural variant might be considered as a potential modulator of this causative pathway.

Mendelian Randomisation Confirms the Role of Y-Chromosome Loss in Alzheimer's Disease Aetiopathogenesis in Men.

Mosaic loss of chromosome Y (mLOY) is a common ageing-related somatic event and has been previously associated with Alzheimer's disease (AD). However, mLOY estimation from genotype microarray data only reflects the mLOY degree of subjects at the moment of DNA sampling. Therefore, mLOY phenotype associations with AD can be severely age-confounded in the context of genome-wide association studies. Here, we applied Mendelian randomisation to construct an age-independent mLOY polygenic risk score (mloy-PRS) using 114 autosomal variants. The mloy-PRS instrument was associated with an 80% increase in mLOY risk per standard deviation unit (p = 4.22 × 10-20) and was orthogonal with age. We found that a higher genetic risk for mLOY was associated with faster progression to AD in men with mild cognitive impairment (hazard ratio (HR) = 1.23, p = 0.01). Importantly, mloy-PRS had no effect on AD conversion or risk in the female group, suggesting that these associations are caused by the inherent loss of the Y chromosome. Additionally, the blood mLOY phenotype in men was associated with increased cerebrospinal fluid levels of total tau and phosphorylated tau181 in subjects with mild cognitive impairment and dementia. Our results strongly suggest that mLOY is involved in AD pathogenesis.

Validating and automating learning of cardiometabolic polygenic risk scores from direct-to-consumer genetic and phenotypic data: implications for scaling precision health research.

INTRODUCTION: A major challenge to enabling precision health at a global scale is the bias between those who enroll in state sponsored genomic research and those suffering from chronic disease. More than 30 million people have been genotyped by direct-to-consumer (DTC) companies such as 23andMe, Ancestry DNA, and MyHeritage, providing a potential mechanism for democratizing access to medical interventions and thus catalyzing improvements in patient outcomes as the cost of data acquisition drops. However, much of these data are sequestered in the initial provider network, without the ability for the scientific community to either access or validate. Here, we present a novel geno-pheno platform that integrates heterogeneous data sources and applies learnings to common chronic disease conditions including Type 2 diabetes (T2D) and hypertension. METHODS: We collected genotyped data from a novel DTC platform where participants upload their genotype data files and were invited to answer general health questionnaires regarding cardiometabolic traits over a period of 6 months. Quality control, imputation, and genome-wide association studies were performed on this dataset, and polygenic risk scores were built in a case-control setting using the BASIL algorithm. RESULTS: We collected data on N = 4,550 (389 cases / 4,161 controls) who reported being affected or previously affected for T2D and N = 4,528 (1,027 cases / 3,501 controls) for hypertension. We identified 164 out of 272 variants showing identical effect direction to previously reported genome-significant findings in Europeans. Performance metric of the PRS models was AUC = 0.68, which is comparable to previously published PRS models obtained with larger datasets including clinical biomarkers. DISCUSSION: DTC platforms have the potential of inverting research models of genome sequencing and phenotypic data acquisition. Quality control (QC) mechanisms proved to successfully enable traditional GWAS and PRS analyses. The direct participation of individuals has shown the potential to generate rich datasets enabling the creation of PRS cardiometabolic models. More importantly, federated learning of PRS from reuse of DTC data provides a mechanism for scaling precision health care delivery beyond the small number of countries who can afford to finance these efforts directly. CONCLUSIONS: The genetics of T2D and hypertension have been studied extensively in controlled datasets, and various polygenic risk scores (PRS) have been developed. We developed predictive tools for both phenotypes trained with heterogeneous genotypic and phenotypic data generated outside of the clinical environment and show that our methods can recapitulate prior findings with fidelity. From these observations, we conclude that it is possible to leverage DTC genetic repositories to identify individuals at risk of debilitating diseases based on their unique genetic landscape so that informed, timely clinical interventions can be incorporated.

Deconvoluting complex correlates of COVID-19 severity with a multi-omic pandemic tracking strategy.

The SARS-CoV-2 pandemic has differentially impacted populations across race and ethnicity. A multi-omic approach represents a powerful tool to examine risk across multi-ancestry genomes. We leverage a pandemic tracking strategy in which we sequence viral and host genomes and transcriptomes from nasopharyngeal swabs of 1049 individuals (736 SARS-CoV-2 positive and 313 SARS-CoV-2 negative) and integrate them with digital phenotypes from electronic health records from a diverse catchment area in Northern California. Genome-wide association disaggregated by admixture mapping reveals novel COVID-19-severity-associated regions containing previously reported markers of neurologic, pulmonary and viral disease susceptibility. Phylodynamic tracking of consensus viral genomes reveals no association with disease severity or inferred ancestry. Summary data from multiomic investigation reveals metagenomic and HLA associations with severe COVID-19. The wealth of data available from residual nasopharyngeal swabs in combination with clinical data abstracted automatically at scale highlights a powerful strategy for pandemic tracking, and reveals distinct epidemiologic, genetic, and biological associations for those at the highest risk.

New insights into the genetic etiology of Alzheimer's disease and related dementias.

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.

Global Biobank Meta-analysis Initiative: Powering genetic discovery across human disease.

Biobanks facilitate genome-wide association studies (GWASs), which have mapped genomic loci across a range of human diseases and traits. However, most biobanks are primarily composed of individuals of European ancestry. We introduce the Global Biobank Meta-analysis Initiative (GBMI)-a collaborative network of 23 biobanks from 4 continents representing more than 2.2 million consented individuals with genetic data linked to electronic health records. GBMI meta-analyzes summary statistics from GWASs generated using harmonized genotypes and phenotypes from member biobanks for 14 exemplar diseases and endpoints. This strategy validates that GWASs conducted in diverse biobanks can be integrated despite heterogeneity in case definitions, recruitment strategies, and baseline characteristics. This collaborative effort improves GWAS power for diseases, benefits understudied diseases, and improves risk prediction while also enabling the nomination of disease genes and drug candidates by incorporating gene and protein expression data and providing insight into the underlying biology of human diseases and traits.

Mitochondrial DNA and Alzheimer's disease: a first case-control study of the Tunisian population.

BACKGROUND: Alzheimer's disease (AD) is the most common neurodegenerative disorder in humans and presents a major health problem throughout the world. The etiology of AD is complex, and many factors are implicated, including mitochondria. Mitochondrial alteration has been proposed as a possible cause of AD. Therefore, several studies have focused on finding an association between inherited mitochondrial DNA variants and AD onset. METHODS: In this study, we looked, for the first time, for a potential association between mitochondrial haplogroups or polymorphisms and AD in the Tunisian population. We also evaluated the distribution of the major genetic risk factor for AD, the apolipoprotein E epsilon 4 (APOE ε4), in this population. In total, 159 single-nucleotide polymorphisms (SNPs) of mitochondrial DNA haplogroups were genotyped in 254 individuals (58 patients and 196 controls). An additional genotyping of APOE ε4 was performed. RESULTS: No significant association between mitochondrial haplogroups and AD was found. However, two individual SNPs, A5656G (p = 0.03821, OR = 10.46) and A13759G (p = 0.03719, OR = 10.78), showed a significant association with AD. APOE 4 was confirmed as a risk factor for AD (p = 0.000014). CONCLUSION: Our findings may confirm the absence of a relation between mitochondrial haplogroups and AD and support the possible involvement of some inherited variants in the pathogenicity of AD.

Neuropsychiatric Profile as a Predictor of Cognitive Decline in Mild Cognitive Impairment.

Introduction: Mild cognitive impairment is often associated with affective and other neuropsychiatric symptoms (NPS). This co-occurrence might have a relevant impact on disease progression, from MCI to dementia. Objective: The aim of this study was to explore the trajectories of cognitive decline in an MCI sample from a memory clinic, taking into consideration a perspective of isolated cognitive functions and based on NPS clusters, accounting for the different comorbid symptoms collected at their baseline visit. Methods: A total of 2,137 MCI patients were monitored over a 2.4-year period. Four clusters of NPS (i.e., Irritability, Apathy, Anxiety/Depression and Asymptomatic) were used to run linear mixed models to explore the interaction of cluster with time on cognitive trajectories using a comprehensive neuropsychological battery (NBACE) administered at baseline and at the three subsequent follow-ups. Results: A significant interaction between cluster and time in cognitive decline was found when verbal learning and cued-recall were explored (p = 0.002 for both memory functions). For verbal learning, the Irritability cluster had the largest effect size (0.69), whereas the Asymptomatic cluster showed the smallest effect size (0.22). For cued-recall, the Irritability cluster had the largest effect size among groups (0.64), and Anxiety/Depression had the smallest effect size (0.21). Conclusions: In MCI patients, the Irritability and Apathy NPS clusters shared similar patterns of worsening in memory functioning, which could point to these NPS as risk factors of a faster cognitive decline, acting as early prognostic markers and helping in the diagnostic process.

Common variants in Alzheimer's disease and risk stratification by polygenic risk scores.

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.

Genome-wide association identifies the first risk loci for psychosis in Alzheimer disease.

Psychotic symptoms, defined as the occurrence of delusions or hallucinations, are frequent in Alzheimer disease (AD with psychosis, AD + P). AD + P affects ~50% of individuals with AD, identifies a subgroup with poor outcomes, and is associated with a greater degree of cognitive impairment and depressive symptoms, compared to subjects without psychosis (AD - P). Although the estimated heritability of AD + P is 61%, genetic sources of risk are unknown. We report a genome-wide meta-analysis of 12,317 AD subjects, 5445 AD + P. Results showed common genetic variation accounted for a significant portion of heritability. Two loci, one in ENPP6 (rs9994623, O.R. (95%CI) 1.16 (1.10, 1.22), p = 1.26 × 10-8) and one spanning the 3'-UTR of an alternatively spliced transcript of SUMF1 (rs201109606, O.R. 0.65 (0.56-0.76), p = 3.24 × 10-8), had genome-wide significant associations with AD + P. Gene-based analysis identified a significant association with APOE, due to the APOE risk haplotype ε4. AD + P demonstrated negative genetic correlations with cognitive and educational attainment and positive genetic correlation with depressive symptoms. We previously observed a negative genetic correlation with schizophrenia; instead, we now found a stronger negative correlation with the related phenotype of bipolar disorder. Analysis of polygenic risk scores supported this genetic correlation and documented a positive genetic correlation with risk variation for AD, beyond the effect of ε4. We also document a small set of SNPs likely to affect risk for AD + P and AD or schizophrenia. These findings provide the first unbiased identification of the association of psychosis in AD with common genetic variation and provide insights into its genetic architecture.

Multiomics integrative analysis identifies APOE allele-specific blood biomarkers associated to Alzheimer's disease etiopathogenesis.

Alzheimer's disease (AD) is the most common form of dementia, currently affecting 35 million people worldwide. Apolipoprotein E (APOE) ε4 allele is the major risk factor for sporadic, late-onset AD (LOAD), which comprises over 95% of AD cases, increasing the risk of AD 4-12 fold. Despite this, the role of APOE in AD pathogenesis is still a mystery. Aiming for a better understanding of APOE-specific effects, the ADAPTED consortium analysed and integrated publicly available data of multiple OMICS technologies from both plasma and brain stratified by APOE haplotype (APOE2, APOE3 and APOE4). Combining genome-wide association studies (GWAS) with differential mRNA and protein expression analyses and single-nuclei transcriptomics, we identified genes and pathways contributing to AD in both APOE dependent and independent fashion. Interestingly, we characterised a set of biomarkers showing plasma and brain consistent protein profiles and opposite trends in APOE2 and APOE4 AD cases that could constitute screening tools for a disease that lacks specific blood biomarkers. Beside the identification of APOE-specific signatures, our findings advocate that this novel approach, based on the concordance across OMIC layers and tissues, is an effective strategy for overcoming the limitations of often underpowered single-OMICS studies.

Neuropsychiatric profiles and conversion to dementia in mild cognitive impairment, a latent class analysis.

Neuropsychiatric symptoms (NPS) have been recently addressed as risk factors of conversion to Alzheimer's disease (AD) and other dementia types in patients diagnosed with Mild Cognitive Impairment (MCI). Our aim was to determine profiles based on the prominent NPS in MCI patients and to explore the predictive value of these profiles on conversion to specific types of dementia. A total of 2137 MCI patients monitored in a memory clinic were included in the study. Four NPS profiles emerged (classes), which were defined by preeminent symptoms: Irritability, Apathy, Anxiety/Depression and Asymptomatic. Irritability and Apathy were predictors of conversion to dementia (HR = 1.43 and 1.56, respectively). Anxiety/depression class showed no risk effect of conversion when compared to Asymptomatic class. Irritability class appeared as the most discriminant neuropsychiatric condition to identify non-AD converters (i.e., frontotemporal dementia, vascular dementia, Parkinson's disease and dementia with Lewy Bodies). The findings revealed that consistent subgroups of MCI patients could be identified among comorbid basal NPS. The preeminent NPS showed to behave differentially on conversion to dementia, beyond AD. Therefore, NPS should be used as early diagnosis facilitators, and should also guide clinicians to detect patients with different illness trajectories in the progression of MCI.

Long runs of homozygosity are associated with Alzheimer's disease.

Long runs of homozygosity (ROH) are contiguous stretches of homozygous genotypes, which are a footprint of inbreeding and recessive inheritance. The presence of recessive loci is suggested for Alzheimer's disease (AD); however, their search has been poorly assessed to date. To investigate homozygosity in AD, here we performed a fine-scale ROH analysis using 10 independent cohorts of European ancestry (11,919 AD cases and 9181 controls.) We detected an increase of homozygosity in AD cases compared to controls [ßAVROH (CI 95%) = 0.070 (0.037-0.104); P = 3.91 × 10-5; ßFROH (CI95%) = 0.043 (0.009-0.076); P = 0.013]. ROHs increasing the risk of AD (OR > 1) were significantly overrepresented compared to ROHs increasing protection (p < 2.20 × 10-16). A significant ROH association with AD risk was detected upstream the HS3ST1 locus (chr4:11,189,482‒11,305,456), (ß (CI 95%) = 1.09 (0.48 ‒ 1.48), p value = 9.03 × 10-4), previously related to AD. Next, to search for recessive candidate variants in ROHs, we constructed a homozygosity map of inbred AD cases extracted from an outbred population and explored ROH regions in whole-exome sequencing data (N = 1449). We detected a candidate marker, rs117458494, mapped in the SPON1 locus, which has been previously associated with amyloid metabolism. Here, we provide a research framework to look for recessive variants in AD using outbred populations. Our results showed that AD cases have enriched homozygosity, suggesting that recessive effects may explain a proportion of AD heritability.

The BDNFVal66Met SNP modulates the association between beta-amyloid and hippocampal disconnection in Alzheimer's disease.

In Alzheimer's disease (AD), a single-nucleotide polymorphism in the gene encoding brain-derived neurotrophic factor (BDNFVal66Met) is associated with worse impact of primary AD pathology (beta-amyloid, Aß) on neurodegeneration and cognitive decline, rendering BDNFVal66Met an important modulating factor of cognitive impairment in AD. However, the effect of BDNFVal66Met on functional networks that may underlie cognitive impairment in AD is poorly understood. Using a cross-validation approach, we first explored in subjects with autosomal dominant AD (ADAD) from the Dominantly Inherited Alzheimer Network (DIAN) the effect of BDNFVal66Met on resting-state fMRI assessed functional networks. In seed-based connectivity analysis of six major large-scale networks, we found a stronger decrease of hippocampus (seed) to medial-frontal connectivity in the BDNFVal66Met carriers compared to BDNFVal homozogytes. BDNFVal66Met was not associated with connectivity in any other networks. Next, we tested whether the finding of more pronounced decrease in hippocampal-medial-frontal connectivity in BDNFVal66Met could be also found in elderly subjects with sporadically occurring Aß, including a group with subjective cognitive decline (N = 149, FACEHBI study) and a group ranging from preclinical to AD dementia (N = 114, DELCODE study). In both of these independently recruited groups, BDNFVal66Met was associated with a stronger effect of more abnormal Aß-levels (assessed by biofluid-assay or amyloid-PET) on hippocampal-medial-frontal connectivity decreases, controlled for hippocampus volume and other confounds. Lower hippocampal-medial-frontal connectivity was associated with lower global cognitive performance in the DIAN and DELCODE studies. Together these results suggest that BDNFVal66Met is selectively associated with a higher vulnerability of hippocampus-frontal connectivity to primary AD pathology, resulting in greater AD-related cognitive impairment.

Interaction of neuropsychiatric symptoms with APOE ε4 and conversion to dementia in MCI patients in a Memory Clinic.

To date, very few studies have been focused on the impact of the convergence of neuropsychiatric symptoms (NPS) and APOE ε4 on the conversion to dementia in patients with Mild Cognitive Impairment patients (MCI), and none has been based in a clinical setting. The objective of the study is to determine the predictive value of additive and multiplicative interactions of NPS and APOE ε4 status on the prediction of incident dementia among MCI patients monitored in a Memory Clinic. 1512 patients (aged 60 and older) with prevalent MCI were followed for a mean of 2 years. Neuropsychiatric symptoms were assessed at baseline using the Neuropsychiatric Inventory Questionnaire. Cox proportional hazards models were calculated. Additive interactions for depression, apathy, anxiety, agitation, appetite, or irritability and a positive ε4 carrier status were obtained, significantly increasing the hazard ratios of incident dementia (HR range 1.3-2.03). Synergistic interactions between NPS and APOE ε4 are identified among MCI patients when predicting incident dementia. The combination of the behavioral status and the genetic trait could be considered a useful strategy to identify the most vulnerable MCI patients to dementia conversion in a Memory Clinic.

Association between retinal thickness and ß-amyloid brain accumulation in individuals with subjective cognitive decline: Fundació ACE Healthy Brain Initiative.

BACKGROUND: Optical coherence tomography (OCT) of the retina is a fast and easily accessible tool for the quantification of retinal structural measurements. Multiple studies show that patients with Alzheimer's disease (AD) exhibit thinning in several retinal layers compared to age-matched controls. Subjective cognitive decline (SCD) has been proposed as a risk factor for progression to AD. There is little data about retinal changes in preclinical AD and their correlation with amyloid-ß (Aß) uptake. AIMS: We investigated the association of retinal thickness quantified by OCT with Aß accumulation and conversion to mild cognitive impairment (MCI) over 24 months in individuals with SCD. METHODS: One hundred twenty-nine individuals with SCD enrolled in Fundació ACE Healthy Brain Initiative underwent comprehensive neuropsychological testing, OCT scan of the retina and florbetaben (FBB) positron emission tomography (PET) at baseline (v0) and after 24 months (v2). We assessed the association of sixteen retinal thickness measurements at baseline with FBB-PET status (+/-) and global standardize uptake value ratio (SUVR) as a continuous measure at v0 and v2 and their predictive value on clinical status change (conversion to mild cognitive impairment (MCI)) at v2. RESULTS: Mean age of the sample was 64.72 ± 7.27 years; 62.8% were females. Fifteen participants were classified as FBB-PET+ at baseline and 22 at v2. Every 1 µm of increased thickness in the inner nasal macular region conferred 8% and 6% higher probability of presenting a FBB-PET+ status at v0 (OR = 1.08, 95% CI = 1.02-1.14, p = 0.007) and v2 (OR = 1.06, 95% CI = 1.02-1.11, p = 0.004), respectively. Inner nasal macular thickness also positively correlated with global SUVR (at v0: ß = 0.23, p = 0.004; at v2: ß = 0.26, p = 0.001). No retinal measurements were associated to conversion to MCI over 24 months. CONCLUSIONS: Subtle retinal thickness changes in the macular region are already present in SCD and correlate with Aß uptake.

Evaluation of macular thickness and volume tested by optical coherence tomography as biomarkers for Alzheimer's disease in a memory clinic.

Building on previous studies that report thinning of the macula in Alzheimer's disease (AD) and mild cognitive impairment (MCI) patients, the use of optical coherence tomography (OCT) has been proposed as a potential biomarker for AD. However, other studies contradict these results. A total of 930 participants (414 cognitively healthy people, 192 with probable amnestic MCI, and 324 probable AD patients) from a memory clinic were consecutively included in this study and underwent a spectral domain OCT scan (Maestro, Topcon) to assess total macular volume and thickness. Macular width measurements were also taken in several subregions (central, inner, and outer rings) and in layers such as the retinal nerve fiber (RNFL) and ganglion cell (CGL). The study employed a design of high ecological validity, with adjustment by age, education, sex, and OCT image quality. AD, MCI, and control groups did not significantly vary with regard to volume and retinal thickness in different layers. When these groups were compared, multivariate-adjusted analysis disclosed no significant differences in total (p = 0.564), CGL (p = 0.267), RNFL (p = 0.574), and macular thickness and volume (p = 0.380). The only macular regions showing significant differences were the superior (p = 0.040) and nasal (p = 0.040) sectors of the inner macular ring. However, adjustment for multiple comparisons nullified this significance. These results are not supporting existing claims for the usefulness of macular thickness as a biomarker of cognitive impairment in a memory unit. OCT biomarkers for AD should be subject to further longitudinal testing.

Genetic architecture of neurodegenerative dementias.

Molecular genetics has been an invaluable tool to help understand the molecular basis of neurodegenerative dementias. In this review, we provide an overview of the genetic architecture underlying some of the most prevalent causes of dementia, including Alzheimer's dementia, frontotemporal lobar degeneration, Lewy body dementia, and prion diseases. We also discuss the complexity of the human genome and how the novel technologies have revolutionized and accelerated the way we screen the variety of our DNA. Finally, we also provide some examples about how this genetic knowledge is being transferred into the clinic through personalized medicine. This article is part of the special issue entitled 'The Quest for Disease-Modifying Therapies for Neurodegenerative Disorders'.