Genome-wide mapping of IBD segments in an Ashkenazi PD cohort identifies associated haplotypes

TMEM16F regulates pathologic α-synuclein secretion and spread in cellular and mouse models of Parkinson's disease

One of the main hallmarks of Parkinson's disease (PD) pathology is the spread of the aggregate-prone protein α-synuclein (α-syn), which can be detected in the plasma and cerebrospinal fluid of patients as well as in the extracellular environment of neuronal cells. The secreted α-syn can exhibit "prion-like" behavior and transmission to naïve cells can promote conformational changes and pathology. The precise role of plasma membrane proteins in the pathologic process of α-syn is yet to be fully resolved. The TMEM16 family of lipid scramblases and ion channels has been recently associated with cancer and infectious diseases but is less known for its role in aging-related diseases. To elucidate the role of TMEM16F in α-syn spread, we transduced neurons derived from TMEM16F knockout mice with a reporter system that enables the distinction between donor and recipient neurons of pathologic α-synA53T. We found that the spread of α-synA53T was reduced in neurons derived from TMEM16F-knockout mice. These findings were recapitulated in vivo in a mouse model of PD, where attenuated α-synA53T spread was observed when TMEM16F was ablated. Moreover, we identified a single nucleotide polymorphism in TMEM16F of Ashkenazi Jewish PD patients resulting in a missense Ala703Ser mutation with enhanced lipid scramblase activity. This mutation is associated with altered regulation of α-synA53T extracellular secretion in cellular models of PD. Our study highlights TMEM16F as a novel regulator of α-syn spread and as a potential therapeutic target in synucleinopathies.

MAPT Locus in Parkinson's Disease Patients of Ashkenazi Origin: A Stratified Analysis

Introduction: MAPT locus is associated with Parkinson's disease (PD), which is located within a large inversion region of high linkage disequilibrium (LD). We aimed to determine whether the H2-haplotype protective effect and its effect size depends on the GBA1 or LRRK2 risk allele carrier status, and to further characterize genetic alterations that might contribute to its effect. Methods: LD analysis was performed using whole-genome sequencing data of 202 unrelated Ashkenazi Jewish (AJ) PDs. A haplotype-divergent variant was genotyped in a cohort of 1200 consecutively recruited AJ-PDs. The odd ratios were calculated using AJ-non-neuro cases from the gnomAD database as the controls in an un-stratified and a stratified manner according to the mutation carrier status, and the effect on the Age at Motor Symptom Onset (AMSO) was examined. Expression and splicing quantitative trait locus (eQTL and sQTL) analyses were carried out using brain tissues from a database. Results: The H2 haplotype exhibited significant association with PD protection, with a similar effect size in GBA1 carriers, LRRK2-G2019S carriers, and non-carriers (OR = 0.77, 0.69, and 0.82, respectively), and there was no effect on AMSO. The LD interval was narrowed to approximately 1.2 Mb. The H2 haplotype carried potential variants in candidate genes (MAPT and SPPL2C); structural deletions and segmental duplication (KANSL1); and variants affecting gene expression and intron excision ratio in brain tissues (LRRC37A/2). Conclusions: Our results demonstrate that H2 is associated with PD and its protective effect is not influenced by the GBA1/LRRK2 risk allele carrier status. This effect may be genetically complex, resulting from different levels of variations such as missense mutations in relevant genes, structural variations, epigenetic modifications, and RNA expression changes, which may operate independently or in synergy.

FiMAP: A fast identity-by-descent mapping test for biobank-scale cohorts

Although genome-wide association studies (GWAS) have identified tens of thousands of genetic loci, the genetic architecture is still not fully understood for many complex traits. Most GWAS and sequencing association studies have focused on single nucleotide polymorphisms or copy number variations, including common and rare genetic variants. However, phased haplotype information is often ignored in GWAS or variant set tests for rare variants. Here we leverage the identity-by-descent (IBD) segments inferred from a random projection-based IBD detection algorithm in the mapping of genetic associations with complex traits, to develop a computationally efficient statistical test for IBD mapping in biobank-scale cohorts. We used sparse linear algebra and random matrix algorithms to speed up the computation, and a genome-wide IBD mapping scan of more than 400,000 samples finished within a few hours. Simulation studies showed that our new method had well-controlled type I error rates under the null hypothesis of no genetic association in large biobank-scale cohorts, and outperformed traditional GWAS single-variant tests when the causal variants were untyped and rare, or in the presence of haplotype effects. We also applied our method to IBD mapping of six anthropometric traits using the UK Biobank data and identified a total of 3,442 associations, 2,131 (62%) of which remained significant after conditioning on suggestive tag variants in the ± 3 centimorgan flanking regions from GWAS.

A genome-wide association study coupled with machine learning approaches to identify influential demographic and genomic factors underlying Parkinson's disease

Background: Despite the recent success of genome-wide association studies (GWAS) in identifying 90 independent risk loci for Parkinson's disease (PD), the genomic underpinning of PD is still largely unknown. At the same time, accurate and reliable predictive models utilizing genomic or demographic features are desired in the clinic for predicting the risk of Parkinson's disease. Methods: To identify influential demographic and genomic factors associated with PD and to further develop predictive models, we utilized demographic data, incorporating 200 variables across 33,473 participants, along with genomic data involving 447,089 SNPs across 8,840 samples, both derived from the Fox Insight online study. We first applied correlation and GWAS analyses to find the top demographic and genomic factors associated with PD, respectively. We further developed and compared a variety of machine learning (ML) models for predicting PD. From the developed ML models, we performed feature importance analysis to reveal the predictability of each demographic or the genomic input feature for PD. Finally, we performed gene set enrichment analysis on our GWAS results to identify PD-associated pathways. Results: In our study, we identified both novel and well-known demographic and genetic factors (along with the enriched pathways) related to PD. In addition, we developed predictive models that performed robustly, with AUC = 0.89 for demographic data and AUC = 0.74 for genomic data. Our GWAS analysis identified several novel and significant variants and gene loci, including three intron variants in LMNA (p-values smaller than 4.0e-21) and one missense variant in SEMA4A (p-value = 1.11e-26). Our feature importance analysis from the PD-predictive ML models highlighted some significant and novel variants from our GWAS analysis (e.g., the intron variant rs1749409 in the RIT1 gene) and helped identify potentially causative variants that were missed by GWAS, such as rs11264300, a missense variant in the gene DCST1, and rs11584630, an intron variant in the gene KCNN3. Conclusion: In summary, by combining a GWAS with advanced machine learning models, we identified both known and novel demographic and genomic factors as well as built well-performing ML models for predicting Parkinson's disease.

Novel variants in genes related to vesicle-mediated-transport modify Parkinson's disease risk

OBJECTIVES

VPS35 and VPS13 have been associated with Parkinson's disease (PD), and their shared phenotype in yeast when reduced in function is abnormal vacuolar transport. We aim to test if additional potentially deleterious variants in other genes that share this phenotype can modify the risk for PD.

METHODS

77 VPS and VPS-related genes were analyzed using whole-genome-sequencing data from 202 PD patients of Ashkenazi Jewish (AJ) ancestry. Filtering was done based on quality and functionality scores. Ten variants in nine genes were further genotyped in 1200 consecutively recruited unrelated AJ-PD patients, and allele frequencies and odds ratio calculated compared to gnomAD-AJ-non-neuro database, in un-stratified (n = 1200) and stratified manner (LRRK2-G2019S-PD patients (n = 145), GBA-PD patients (n = 235), and non-carriers of these mutations (NC, n = 787)).

RESULTS

Five variants in PIK3C3, VPS11, AP1G2, HGS and VPS13D were significantly associated with PD-risk. PIK3C3-R768W showed a significant association in an un-stratified (all PDs) analysis, as well as in stratified (LRRK2, GBA, and NC) analyses (Odds ratios = 2.71, 5.32, 3.26. and 2.19 with p = 0.0015, 0.002, 0.0287, and 0.0447, respectively). AP1G2-R563W was significantly associated in LRRK2-carriers (OR = 3.69, p = 0.006) while VPS13D-D2932N was significantly associated in GBA-carriers (OR = 5.45, p = 0.0027). VPS11-C846G and HGS-S243Y were significantly associated in NC (OR = 2.48 and 2.06, with p = 0.022 and 0.0163, respectively).

CONCLUSIONS

Variants in genes involved in vesicle-mediated protein transport and recycling pathways, including autophagy and mitophagy, may differentially modify PD-risk in LRRK2-carriers, GBA carriers, or NC. Specifically, PIK3C3-R768W is a PD-risk allele, with the highest effect size in LRRK2-G2019S carriers. These results suggest oligogenic effect that may depends on the genetic background of the patient. An unbiased burden of mutations approach in these genes should be evaluated in additional PD and control groups. The mechanisms by which these novel variants interact and increase PD-risk should be researched in depth for better tailoring therapeutic intervention for PD prevention or slowing disease progression.

Variants in PSMB9 and FGR differentially affect Parkinson's disease risk in GBA and LRRK2 mutation carriers

INTRODUCTION

Recent studies found an association between Parkinson's disease (PD) and alterations in the innate immune system. However, whether the involvement of this system in two of the known genetic forms of PD, GBA-PD and LRRK2-PD, and in patients who do not carry these mutations is different, is yet to be determined. We aimed to test if genetic variations in the innate immune genes are differentially associated with PD in these subgroups.

METHODS

Innate immune genes were identified and classified into sub-lists according to Reactome pathways. Whole-genome-sequencing (WGS) was performed on 201 unrelated Ashkenazi-Jewish (AJ) PD patients including 104 GBA-PD, 32 LRRK2-PD, and 65 non-carriers-PD (NC-PD). To identify genes with different burden between these subgroups of PD, gene-based Sequence kernel association optimal unified test (SKAT-O) analysis was performed on innate immune pathways. Candidate variants within the significant genes were further genotyped in a cohort of 1200 unrelated, consecutively recruited, AJ-PD patients, and to evaluate their association with PD-risk their allele frequencies were compared to AJ-non-neuro cases in gnomAD database, in a stratified and un-stratified manner.

RESULTS

SKAT-O analysis showed significantly different burden for PSMB9 (GBA-PD versus NC-PD) and FGR (GBA-PD versus LRRK2-PD). Two candidate variants in PSMB9 showed an association with GBA-PD-risk and NC-PD-risk while one FGR variant showed an association with LRRK2-PD-risk.

CONCLUSION

Our data supports differential involvement of innate immunity risk alleles in PD and emphasizes the differences between the GBA- and LRRK2-PD subgroups.

Open-source benchmarking of IBD segment detection methods for biobank-scale cohorts

In the recent biobank era of genetics, the problem of identical-by-descent (IBD) segment detection received renewed interest, as IBD segments in large cohorts offer unprecedented opportunities in the study of population and genealogical history, as well as genetic association of long haplotypes. While a new generation of efficient methods for IBD segment detection becomes available, direct comparison of these methods is difficult: existing benchmarks were often evaluated in different datasets, with some not openly accessible; methods benchmarked were run under suboptimal parameters; and benchmark performance metrics were not defined consistently. Here, we developed a comprehensive and completely open-source evaluation of the power, accuracy, and resource consumption of these IBD segment detection methods using realistic population genetic simulations with various settings. Our results pave the road for fair evaluation of IBD segment detection methods and provide an practical guide for users.

The Big Picture of Neurodegeneration: A Meta Study to Extract the Essential Evidence on Neurodegenerative Diseases in a Network-Based Approach

The common features of all neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, Amyotrophic Lateral Sclerosis (ALS), and Huntington's disease, are the accumulation of aggregated and misfolded proteins and the progressive loss of neurons, leading to cognitive decline and locomotive dysfunction. Still, they differ in their ultimate manifestation, the affected brain region, and the kind of proteinopathy. In the last decades, a vast number of processes have been described as associated with neurodegenerative diseases, making it increasingly harder to keep an overview of the big picture forming from all those data. In this meta-study, we analyzed genomic, transcriptomic, proteomic, and epigenomic data of the aforementioned diseases using the data of 234 studies in a network-based approach to study significant general coherences but also specific processes in individual diseases or omics levels. In the analysis part, we focus on only some of the emerging findings, but trust that the meta-study provided here will be a valuable resource for various other researchers focusing on specific processes or genes contributing to the development of neurodegeneration.

Common variants contribute to intrinsic human brain functional networks

The human brain forms functional networks of correlated activity, which have been linked with both cognitive and clinical outcomes. However, the genetic variants affecting brain function are largely unknown. Here, we used resting-state functional magnetic resonance images from 47,276 individuals to discover and validate common genetic variants influencing intrinsic brain activity. We identified 45 new genetic regions associated with brain functional signatures (P < 2.8 × 10^-11), including associations to the central executive, default mode, and salience networks involved in the triple-network model of psychopathology. A number of brain activity-associated loci colocalized with brain disorders (e.g., the APOE ε4 locus with Alzheimer's disease). Variation in brain function was genetically correlated with brain disorders, such as major depressive disorder and schizophrenia. Together, our study provides a step forward in understanding the genetic architecture of brain functional networks and their genetic links to brain-related complex traits and disorders.

Replication of chromosomal loci involved in Parkinson's disease: A quantitative synthesis of GWAS

•

The first quantitative synthesis of GWAS regarding Parkinson’s Disease.

•

Fifteen Parkinson’s Disease GWASs with 191.397 available SNPs pooled.

•

User friendly software (METRADISC-XL) implemented.

•

Seven chromosomal regions (bins) were replicated as associated with the Parkinson’s Disease trait.

Introduction

Parkinson’s disease is a neurodegenerative disorder with a complex etiology coming from interactions between genetic and environmental factors. Research on Parkinson’s disease genetics has been an effortful struggle, while new technologies and novel study designs served as indispensable boosters. Until now, 90 loci and 20 disease-causing gene mutations have been identified. In this study we describe a novel non-parametric approach to GWAS meta-analysis and its application in PD genetics.

Methods

A literature search was conducted to identify Genome-Wide Association Studies (GWAS) regarding Parkinson’s disease. We applied predefined inclusion criteria and extracted the reported SNPs and their respective position and statistical significance. We divided all chromosomes in approximately equal genetic distance segments called bins and recorded the most significant SNP from each bin and each study and ranked them in terms of their p-value. Ranks from each bin were summed, averaged and added in a heterogeneity-based analysis using the METRADISC-XL software. Weighted and unweighted analysis was performed.

Results

Five-hundred and forty-three SNPs and their respective p-values from 15 studies were matched in their corresponding bins. The METRADISC-XL analysis resulted in 7 bins with a significant p-value. A bin on chromosome 4 where the SNCA gene is located found with genome-wide significant association with Parkinson’s Disease.

Conclusion

This is the first time a non-parametric method is applied in GWAS meta-analysis. The results add some insight on the overall understanding of Parkinson’s disease genetics and serve as a first step of further convergent analysis with Genome-wide linkage studies.

C9orf72-G4C2 Intermediate Repeats and Parkinson's Disease; A Data-Driven Hypothesis

Pathogenic C9orf72-G₄C₂ repeat expansions are associated with ALS/FTD, but not with Parkinson’s disease (PD); yet the possible link between intermediate repeat lengths and PD remains inconclusive. We aim to study the potential involvement of these repeats in PD. The number of C9orf72-repeats were determined by flanking and repeat-primed PCR assays, and the risk-haplotype was determined by SNP-array. Their association with PD was assessed in a stratified manner: in PD-patients-carriers of mutations in LRRK2, GBA, or SMPD1 genes (n = 388), and in PD-non-carriers (NC, n = 718). Allelic distribution was significantly different only in PD-NC compared to 600 controls when looking both at the allele with higher repeat’s size (p = 0.034) and at the combined number of repeats from both alleles (p = 0.023). Intermediate repeats (20–60 repeats) were associated with PD in PD-NC patients (p = 0.041; OR = 3.684 (CI 1.05–13.0)) but not in PD-carriers (p = 0.684). The C9orf72 risk-haplotype, determined in a subgroup of 588 PDs and 126 controls, was observed in higher frequency in PD-NC (dominant model, OR = 1.71, CI 1.04–2.81, p = 0.0356). All 19 alleles within the risk-haplotype were associated with higher C9orf72 RNA levels according to the GTEx database. Based on our data, we suggest a model in which intermediate repeats are a risk factor for PD in non-carriers, driven not only by the number of repeats but also by the variants’ genotypes within the risk-haplotype. Further studies are needed to elucidate this possible role of C9orf72 in PD pathogenesis.

Nucks1 gene polymorphism rs823114 is associated with the positive symptoms and neurocognitive function of patients with schizophrenia in parts of southern China

Nuclear casein kinase and cyclin-dependent kinase substrate 1 (nucks1) are considered a potential susceptibility gene for certain neurological diseases, such as Parkinson's disease (PD). In our study, we genotyped three single nucleotide polymorphisms (SNPs) (rs4951261, rs823114 and rs951366) of the nucks1 gene in 774 schizophrenic patients and 819 healthy controls using the improved multiplex ligation detection reaction (imLDR) technique. Furthermore, we also studied the relationship between the above SNPs and the clinical psychiatric symptoms and neurocognitive function of the patients. Genotype distributions and allele frequencies of these SNPs showed no significant differences and were found between patients and healthy controls. However, in an analysis of the positive symptom score of rs823114 among male patients, we found that the score of the A/A genotype was lower than that of the G/A+G/G genotypes (P = 0.001, P(corr) = 0.003]. Additionally, we also found that among the female patients, G allele carriers with rs823114 had lower semantic fluency scores than subjects with the A/A genotype (P = 0.010, P(corr) = 0.030]. Our data show for the first time that rs823114 polymorphism of nucks1 may affect positive symptoms and neurocognitive function in patients with schizophrenia in parts of southern China.

Fast and Robust Identity-by-Descent Inference with the Templated Positional Burrows-Wheeler Transform

Estimating the genomic location and length of identical-by-descent (IBD) segments among individuals is a crucial step in many genetic analyses. However, the exponential growth in the size of biobank and direct-to-consumer genetic data sets makes accurate IBD inference a significant computational challenge. Here we present the templated positional Burrows-Wheeler transform (TPBWT) to make fast IBD estimates robust to genotype and phasing errors. Using haplotype data simulated over pedigrees with realistic genotyping and phasing errors, we show that the TPBWT outperforms other state-of-the-art IBD inference algorithms in terms of speed and accuracy. For each phase-aware method, we explore the false positive and false negative rates of inferring IBD by segment length and characterize the types of error commonly found. Our results highlight the fragility of most phased IBD inference methods; the accuracy of IBD estimates can be highly sensitive to the quality of haplotype phasing. Additionally, we compare the performance of the TPBWT against a widely used phase-free IBD inference approach that is robust to phasing errors. We introduce both in-sample and out-of-sample TPBWT-based IBD inference algorithms and demonstrate their computational efficiency on massive-scale data sets with millions of samples. Furthermore, we describe the binary file format for TPBWT-compressed haplotypes that results in fast and efficient out-of-sample IBD computes against very large cohort panels. Finally, we demonstrate the utility of the TPBWT in a brief empirical analysis, exploring geographic patterns of haplotype sharing within Mexico. Hierarchical clustering of IBD shared across regions within Mexico reveals geographically structured haplotype sharing and a strong signal of isolation by distance. Our software implementation of the TPBWT is freely available for noncommercial use in the code repository (https://github.com/23andMe/phasedibd, last accessed January 11, 2021).

A Systems Biology Approach for Hypothesizing the Effect of Genetic Variants on Neuroimaging Features in Alzheimer's Disease

BACKGROUND

Neuroimaging markers provide quantitative insight into brain structure and function in neurodegenerative diseases, such as Alzheimer's disease, where we lack mechanistic insights to explain pathophysiology. These mechanisms are often mediated by genes and genetic variations and are often studied through the lens of genome-wide association studies. Linking these two disparate layers (i.e., imaging and genetic variation) through causal relationships between biological entities involved in the disease's etiology would pave the way to large-scale mechanistic reasoning and interpretation.

OBJECTIVE

We explore how genetic variants may lead to functional alterations of intermediate molecular traits, which can further impact neuroimaging hallmarks over a series of biological processes across multiple scales.

METHODS

We present an approach in which knowledge pertaining to single nucleotide polymorphisms and imaging readouts is extracted from the literature, encoded in Biological Expression Language, and used in a novel workflow to assist in the functional interpretation of SNPs in a clinical context.

RESULTS

We demonstrate our approach in a case scenario which proposes KANSL1 as a candidate gene that accounts for the clinically reported correlation between the incidence of the genetic variants and hippocampal atrophy. We find that the workflow prioritizes multiple mechanisms reported in the literature through which KANSL1 may have an impact on hippocampal atrophy such as through the dysregulation of cell proliferation, synaptic plasticity, and metabolic processes.

CONCLUSION

We have presented an approach that enables pinpointing relevant genetic variants as well as investigating their functional role in biological processes spanning across several, diverse biological scales.

Common Factors in Neurodegeneration: A Meta-Study Revealing Shared Patterns on a Multi-Omics Scale

Neurodegenerative diseases such as Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), and amyotrophic lateral sclerosis (ALS) are heterogeneous, progressive diseases with frequently overlapping symptoms characterized by a loss of neurons. Studies have suggested relations between neurodegenerative diseases for many years (e.g., regarding the aggregation of toxic proteins or triggering endogenous cell death pathways). We gathered publicly available genomic, transcriptomic, and proteomic data from 177 studies and more than one million patients to detect shared genetic patterns between the neurodegenerative diseases on three analyzed omics-layers. The results show a remarkably high number of shared differentially expressed genes between the transcriptomic and proteomic levels for all conditions, while showing a significant relation between genomic and proteomic data between AD and PD and AD and ALS. We identified a set of 139 genes being differentially expressed in several transcriptomic experiments of all four diseases. These 139 genes showed overrepresented gene ontology (GO) Terms involved in the development of neurodegeneration, such as response to heat and hypoxia, positive regulation of cytokines and angiogenesis, and RNA catabolic process. Furthermore, the four analyzed neurodegenerative diseases (NDDs) were clustered by their mean direction of regulation throughout all transcriptomic studies for this set of 139 genes, with the closest relation regarding this common gene set seen between AD and HD. GO-Term and pathway analysis of the proteomic overlap led to biological processes (BPs), related to protein folding and humoral immune response. Taken together, we could confirm the existence of many relations between Alzheimer's disease, Parkinson's disease, Huntington's disease, and amyotrophic lateral sclerosis on transcriptomic and proteomic levels by analyzing the pathways and GO-Terms arising in these intersections. The significance of the connection and the striking relation of the results to processes leading to neurodegeneration between the transcriptomic and proteomic data for all four analyzed neurodegenerative diseases showed that exploring many studies simultaneously, including multiple omics-layers of different neurodegenerative diseases simultaneously, holds new relevant insights that do not emerge from analyzing these data separately. Furthermore, the results shed light on processes like the humoral immune response that have previously been described only for certain diseases. Our data therefore suggest human patients with neurodegenerative diseases should be addressed as complex biological systems by integrating multiple underlying data sources.

Network Protein Interaction in Parkinson's Disease and Periodontitis Interplay: A Preliminary Bioinformatic Analysis

Recent studies supported a clinical association between Parkinson's disease (PD) and periodontitis. Hence, investigating possible interactions between proteins associated to these two conditions is of interest. In this study, we conducted a protein-protein network interaction analysis with recognized genes encoding proteins with variants strongly associated with PD and periodontitis. Genes of interest were collected via the Genome-Wide Association Studies (GWAS) database. Then, we conducted a protein interaction analysis, using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database, with a highest confidence cutoff of 0.9 and sensitivity analysis with confidence cutoff of 0.7. Our protein network casts a comprehensive analysis of potential protein-protein interactions between PD and periodontitis. This analysis may underpin valuable information for new candidate molecular mechanisms between PD and periodontitis and may serve new potential targets for research purposes. These results should be carefully interpreted, giving the limitations of this approach.

Exploring the Role of Contactins across Psychological, Psychiatric and Cardiometabolic Traits within UK Biobank

Individuals with severe mental illness have an increased risk of cardiometabolic diseases compared to the general population. Shared risk factors and medication effects explain part of this excess risk; however, there is growing evidence to suggest that shared biology (including genetic variation) is likely to contribute to comorbidity between mental and physical illness. Contactins are a family of genes involved in development of the nervous system and implicated, though genome-wide association studies, in a wide range of psychological, psychiatric and cardiometabolic conditions. Contactins are plausible candidates for shared pathology between mental and physical health. We used data from UK Biobank to systematically assess how genetic variation in contactin genes was associated with a wide range of psychological, psychiatric and cardiometabolic conditions. We also investigated whether associations for cardiometabolic and psychological traits represented the same or distinct signals and how the genetic variation might influence the measured traits. We identified: A novel genetic association between variation in CNTN1 and current smoking; two independent signals in CNTN4 for BMI; and demonstrated that associations between CNTN5 and neuroticism were distinct from those between CNTN5 and blood pressure/HbA1c. There was no evidence that the contactin genes contributed to shared aetiology between physical and mental illness.

Contactin-1 Is Required for Peripheral Innervation and Immune Homeostasis Within the Intestinal Mucosa

Neuronal regulation of diverse physiological functions requires complex molecular interactions in innervated tissues to maintain proper organ function. Here we show that loss of the neuronal cell surface adhesion/recognition molecule Contactin-1 (Cntn1) directly impairs intestinal function causing wasting that subsequently results in global immune defects. Loss of Cntn1 results in hematologic alterations and changes in blood metabolites associated with malnourishment. We found thymus and spleen of Cntn1-deficient animals atrophied with severe reductions in lymphocyte populations. Elevated thymic Gilz expression indicated ongoing glucocorticoid signaling in Cntn1-deficient animals, consistent with the malnourishment phenotype. Intestinal Contactin-1 was localized to neurons in the villi and the submucosal/myenteric plexus that innervates smooth muscle. Loss of Cntn1 was associated with reduced intestinal Bdnf and Adrb2, indicating reduced neuromuscular crosstalk. Additionally, loss of Cntn1 resulted in reduced recruitment of CD3⁺ T cells to villi within the small intestine. Together, these data illustrate the critical role of Contactin-1 function within the gut, and how this is required for normal systemic immune functions.

G2019S-LRRK2 mutation enhances MPTP-linked Parkinsonism in mice

Parkinson's disease (PD) is a common neurodegenerative disease with a heterogeneous etiology that involves genetic and environmental factors or exogenous. Current LRRK2 PD animal models only partly reproduce the characteristics of the disease with very subtle dopaminergic neuron degeneration. We developed a new model of PD that combines a sub-toxic MPTP insult to the G2019S-LRRK2 mutation. Our newly generated mice, overexpressing mutant G2019S-LRRK2 protein in the brain, displayed a mild, age-dependent progressive motor impairment, but no reduction of lifespan. Cortical neurons from G2019S-LRRK2 mice showed an increased vulnerability to stress insults, compared with neurons overexpressing wild-type WT-LRRK2, or non-transgenic (nTg) neurons. The exposure of LRRK2 transgenic mice to a sub-toxic dose of MPTP resulted in severe motor impairment, selective loss of dopamine neurons and increased astrocyte activation, whereas nTg mice with MPTP exposure showed no deficits. Interestingly, mice overexpressing WT-LRRK2 showed a significant impairment that was milder than for the mutant G2019S-LRRK2 mice. L-DOPA treatments could partially improve the movement impairments but did not protect the dopamine neuron loss. In contrast, treatments with an LRRK2 kinase inhibitor significantly reduced the dopaminergic neuron degeneration in this interaction model. Our studies provide a novel LRRK2 gene-MPTP interaction PD mouse model, and a useful tool for future studies of PD pathogenesis and therapeutic intervention.

DNA-mediated dimerization on a compact sequence signature controls enhancer engagement and regulation by FOXA1

FOXA1 is a transcription factor capable to bind silenced chromatin to direct context-dependent cell fate conversion. Here, we demonstrate that a compact palindromic DNA element (termed 'DIV' for its diverging half-sites) induces the homodimerization of FOXA1 with strongly positive cooperativity. Alternative structural models are consistent with either an indirect DNA-mediated cooperativity or a direct protein-protein interaction. The cooperative homodimer formation is strictly constrained by precise half-site spacing. Re-analysis of chromatin immunoprecipitation sequencing data indicates that the DIV is effectively targeted by FOXA1 in the context of chromatin. Reporter assays show that FOXA1-dependent transcriptional activity declines when homodimeric binding is disrupted. In response to phosphatidylinositol-3 kinase inhibition DIV sites pre-bound by FOXA1 such as at the PVT1/MYC locus exhibit a strong increase in accessibility suggesting a role of the DIV configuration in the chromatin closed-open dynamics. Moreover, several disease-associated single nucleotide polymorphisms map to DIV elements and show allelic differences in FOXA1 homodimerization, reporter gene expression and are annotated as quantitative trait loci. This includes the rs541455835 variant at the MAPT locus encoding the Tau protein associated with Parkinson's disease. Collectively, the DIV guides chromatin engagement and regulation by FOXA1 and its perturbation could be linked to disease etiologies.

A study of Kibbutzim in Israel reveals risk factors for cardiometabolic traits and subtle population structure

Genetic studies in isolated populations often increase power for identifying loci associated with complex diseases and traits. We present here the Kibbutzim Family Study (KFS), aimed at investigating the genetic basis of cardiometabolic traits in extended Israeli families characterized by long-term social stability and a homogeneous environment. Extensive information on cardiometabolic traits, as well as genome-wide genotypes, were collected on 901 individuals. We observed that most KFS participants were of Ashkenazi Jewish (AJ) genetic origin, confirmed a recent severe bottleneck in the AJ recent history, and detected a subtle within-AJ population structure. Focusing on genetic variants relatively common in the KFS but very rare in Europeans, we observed that AJ-enriched variants appear in cancer-related pathways more than expected by chance. We conducted an association study of the AJ-enriched variants against 16 cardiometabolic traits, and found seven loci (24 variants) to be significantly associated. The strongest association, which we also replicated in an independent study, was between a variant upstream of MSRA (frequency ≈1% in the KFS and nearly absent in Europeans) and weight (P = 3.6∙10-8). In conclusion, the KFS is a valuable resource for the study of the population genetics of Israel as well as the genetics of cardiometabolic traits.

Advances in the discovery of genetic risk factors for complex forms of neurodegenerative disorders: contemporary approaches, success, challenges and prospects

Neurodegenerative diseases constitute a large proportion of disorders in elderly, majority being sporadic in occurrence with ∼5-10% familial. A strong genetic component underlies the Mendelian forms but nongenetic factors together with genetic vulnerability contributes to the complex sporadic forms. Several gene discoveries in the familial forms have provided novel insights into the pathogenesis of neurodegeneration with implications for treatment. Conversely, findings from genetic dissection of the sporadic forms, despite large genomewide association studies and more recently whole exome and whole genome sequencing, have been limited. This review provides a concise account of the genetics that we know, the pathways that they implicate, the challenges that are faced and the prospects that are envisaged for the sporadic, complex forms of neurodegenerative diseases, taking four most common conditions, namely Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis and Huntington disease as examples. Poor replication across studies, inability to establish genotype-phenotype correlations and the overall failure to predict risk and/or prevent disease in this group poses a continuing challenge. Among others, clinical heterogeneity emerges as the most important impediment warranting newer approaches. Advanced computational and system biology tools to analyse the big data are being generated and the alternate strategy such as subgrouping of case-control cohorts based on deep phenotyping using the principles of Ayurveda to overcome current limitation of phenotype heterogeneity seem to hold promise. However, at this point, with advances in discovery genomics and functional analysis of putative determinants with translation potential for the complex forms being minimal, stem cell therapies are being attempted as potential interventions. In this context, the possibility to generate patient derived induced pluripotent stem cells, mutant/gene/genome correction through CRISPR/Cas9 technology and repopulating the specific brain regions with corrected neurons, which may fulfil the dream of personalized medicine have been mentioned briefly. Understanding disease pathways/biology using this technology, with implications for development of novel therapeutics are optimistic expectations in the near future.

Haplotype Sharing Provides Insights into Fine-Scale Population History and Disease in Finland

Finland provides unique opportunities to investigate population and medical genomics because of its adoption of unified national electronic health records, detailed historical and birth records, and serial population bottlenecks. We assembled a comprehensive view of recent population history (≤100 generations), the timespan during which most rare-disease-causing alleles arose, by comparing pairwise haplotype sharing from 43,254 Finns to that of 16,060 Swedes, Estonians, Russians, and Hungarians from geographically and linguistically adjacent countries with different population histories. We find much more extensive sharing in Finns, with at least one ≥ 5 cM tract on average between pairs of unrelated individuals. By coupling haplotype sharing with fine-scale birth records from more than 25,000 individuals, we find that although haplotype sharing broadly decays with geographical distance, there are pockets of excess haplotype sharing; individuals from northeast Finland typically share several-fold more of their genome in identity-by-descent segments than individuals from southwest regions. We estimate recent effective population-size changes through time across regions of Finland, and we find that there was more continuous gene flow as Finns migrated from southwest to northeast between the early- and late-settlement regions than was dichotomously described previously. Lastly, we show that haplotype sharing is locally enriched by an order of magnitude among pairs of individuals sharing rare alleles and especially among pairs sharing rare disease-causing variants. Our work provides a general framework for using haplotype sharing to reconstruct an integrative view of recent population history and gain insight into the evolutionary origins of rare variants contributing to disease.

Roles of NUCKS1 in Diseases: Susceptibility, Potential Biomarker, and Regulatory Mechanisms

Nuclear casein kinase and cyclin-dependent kinase substrate 1 (NUCKS1) is a 27 kD chromosomal, highly conserved, and vertebrate-specific protein. NUCKS1 gene encodes a nuclear protein and the conserved regions of NUCKS1 contain several consensus phosphorylation sites for casein kinase II (CK2) and cyclin-dependent kinases (Cdk) and a basic DNA-binding domain. NUCKS1 is similar to the high mobility group (HMG) family which dominates chromatin remodeling and regulates gene transcription. Meanwhile, NUCKS1 is a RAD51 associated protein 1 (RAD51AP1) paralog that is significant for homologous recombination (HR) and genome stability and also a transcriptional regulator of the insulin signaling components. NUCKS1 plays an important role in DNA damage response and metabolism, participates in inflammatory immune response, and correlates with microRNA. Although there is still not enough functional information on NUCKS1, evidences suggest that NUCKS1 can be used as the biomarker of several cancers. This review summarizes the latest research on NUCKS1 about its susceptibility in diseases, expression levels, and regulatory mechanisms as well as the possible functions in reference to diseases.

Functional variants in the LRRK2 gene confer shared effects on risk for Crohn's disease and Parkinson's disease

Crohn's disease (CD), a form of inflammatory bowel disease, has a higher prevalence in Ashkenazi Jewish than in non-Jewish European populations. To define the role of nonsynonymous mutations, we performed exome sequencing of Ashkenazi Jewish patients with CD, followed by array-based genotyping and association analysis in 2066 CD cases and 3633 healthy controls. We detected association signals in the LRRK2 gene that conferred risk for CD (N2081D variant, P = 9.5 × 10-10) or protection from CD (N551K variant, tagging R1398H-associated haplotype, P = 3.3 × 10-8). These variants affected CD age of onset, disease location, LRRK2 activity, and autophagy. Bayesian network analysis of CD patient intestinal tissue further implicated LRRK2 in CD pathogenesis. Analysis of the extended LRRK2 locus in 24,570 CD cases, patients with Parkinson's disease (PD), and healthy controls revealed extensive pleiotropy, with shared genetic effects between CD and PD in both Ashkenazi Jewish and non-Jewish cohorts. The LRRK2 N2081D CD risk allele is located in the same kinase domain as G2019S, a mutation that is the major genetic cause of familial and sporadic PD. Like the G2019S mutation, the N2081D variant was associated with increased kinase activity, whereas neither N551K nor R1398H variants on the protective haplotype altered kinase activity. We also confirmed that R1398H, but not N551K, increased guanosine triphosphate binding and hydrolyzing enzyme (GTPase) activity, thereby deactivating LRRK2. The presence of shared LRRK2 alleles in CD and PD provides refined insight into disease mechanisms and may have major implications for the treatment of these two seemingly unrelated diseases.

From Genomics to Omics Landscapes of Parkinson's Disease: Revealing the Molecular Mechanisms

Molecular mechanisms of Parkinson's disease (PD) have already been investigated in various different omics landscapes. We reviewed the literature about different omics approaches between November 2005 and November 2017 to depict the main pathological pathways for PD development. In total, 107 articles exploring different layers of omics data associated with PD were retrieved. The studies were grouped into 13 omics layers: genomics-DNA level, transcriptomics, epigenomics, proteomics, ncRNomics, interactomics, metabolomics, glycomics, lipidomics, phenomics, environmental omics, pharmacogenomics, and integromics. We discussed characteristics of studies from different landscapes, such as main findings, number of participants, sample type, methodology, and outcome. We also performed curation and preliminary synthesis of multiple omics data, and identified overlapping results, which could lead toward selection of biomarkers for further validation of PD risk loci. Biomarkers could support the development of targeted prognostic/diagnostic panels as a tool for early diagnosis and prediction of progression rate and prognosis. This review presents an example of a comprehensive approach to revealing the underlying processes and risk factors of a complex disease. It urges scientists to structure the already known data and integrate it into a meaningful context.

Investigating the genetic architecture of dementia with Lewy bodies: a two-stage genome-wide association study

BACKGROUND

Dementia with Lewy bodies is the second most common form of dementia in elderly people but has been overshadowed in the research field, partly because of similarities between dementia with Lewy bodies, Parkinson's disease, and Alzheimer's disease. So far, to our knowledge, no large-scale genetic study of dementia with Lewy bodies has been done. To better understand the genetic basis of dementia with Lewy bodies, we have done a genome-wide association study with the aim of identifying genetic risk factors for this disorder.

METHODS

In this two-stage genome-wide association study, we collected samples from white participants of European ancestry who had been diagnosed with dementia with Lewy bodies according to established clinical or pathological criteria. In the discovery stage (with the case cohort recruited from 22 centres in ten countries and the controls derived from two publicly available database of Genotypes and Phenotypes studies [phs000404.v1.p1 and phs000982.v1.p1] in the USA), we performed genotyping and exploited the recently established Haplotype Reference Consortium panel as the basis for imputation. Pathological samples were ascertained following autopsy in each individual brain bank, whereas clinical samples were collected after participant examination. There was no specific timeframe for collection of samples. We did association analyses in all participants with dementia with Lewy bodies, and also only in participants with pathological diagnosis. In the replication stage, we performed genotyping of significant and suggestive results from the discovery stage. Lastly, we did a meta-analysis of both stages under a fixed-effects model and used logistic regression to test for association in each stage.

FINDINGS

This study included 1743 patients with dementia with Lewy bodies (1324 with pathological diagnosis) and 4454 controls (1216 patients with dementia with Lewy bodies vs 3791 controls in the discovery stage; 527 vs 663 in the replication stage). Results confirm previously reported associations: APOE (rs429358; odds ratio [OR] 2·40, 95% CI 2·14-2·70; p=1·05 × 10-48), SNCA (rs7681440; OR 0·73, 0·66-0·81; p=6·39 × 10-10), an GBA (rs35749011; OR 2·55, 1·88-3·46; p=1·78 × 10-9). They also provide some evidence for a novel candidate locus, namely CNTN1 (rs7314908; OR 1·51, 1·27-1·79; p=2·32 × 10-6); further replication will be important. Additionally, we estimate the heritable component of dementia with Lewy bodies to be about 36%.

INTERPRETATION

Despite the small sample size for a genome-wide association study, and acknowledging the potential biases from ascertaining samples from multiple locations, we present the most comprehensive and well powered genetic study in dementia with Lewy bodies so far. These data show that common genetic variability has a role in the disease.

FUNDING

The Alzheimer's Society and the Lewy Body Society.

A systematic review and integrative approach to decode the common molecular link between levodopa response and Parkinson's disease

Background

PD is a progressive neurodegenerative disorder commonly treated by levodopa. The findings from genetic studies on adverse effects (ADRs) and levodopa efficacy are mostly inconclusive. Here, we aim to identify predictive genetic biomarkers for levodopa response (LR) and determine common molecular link with disease susceptibility. A systematic review for LR was conducted for ADR, and drug efficacy, independently. All included articles were assessed for methodological quality on 14 parameters. GWAS of PD were also reviewed. Protein-protein interaction (PPI) analysis using STRING and functional enrichment using WebGestalt was performed to explore the common link between LR and PD.

Results

From 37 candidate studies on levodopa toxicity, 18 genes were found associated, of which, CA_n STR 13, 14 (DRD2) was most significantly associated with dyskinesia, followed by rs1801133 (MTHFR) with hyper-homocysteinemia, and rs474559 (HOMER1) with hallucination. Similarly, 8 studies on efficacy resulted in 4 genes in which rs28363170, rs3836790 (SLC6A3) and rs4680 (COMT), were significant. To establish the molecular connection between LR with PD, we identified 35 genes significantly associated with PD. With 19 proteins associated with LR and 35 with PD, two independent PPI networks were constructed. Among the 67 nodes (263 edges) in LR, and 62 nodes (190 edges) in PD pathophysiology, UBC, SNCA, FYN, SRC, CAMK2A, and SLC6A3 were identified as common potential candidates.

Conclusion

Our study revealed the genetically significant polymorphism concerning the ADRs and levodopa efficacy. The six common genes may be used as predictive markers for therapy optimization and as putative drug target candidates.

Electronic supplementary material

The online version of this article (10.1186/s12920-017-0291-0) contains supplementary material, which is available to authorized users.

Genetic identification of a common collagen disease in puerto ricans via identity-by-descent mapping in a health system

Achieving confidence in the causality of a disease locus is a complex task that often requires supporting data from both statistical genetics and clinical genomics. Here we describe a combined approach to identify and characterize a genetic disorder that leverages distantly related patients in a health system and population-scale mapping. We utilize genomic data to uncover components of distant pedigrees, in the absence of recorded pedigree information, in the multi-ethnic BioMe biobank in New York City. By linking to medical records, we discover a locus associated with both elevated genetic relatedness and extreme short stature. We link the gene, COL27A1, with a little-known genetic disease, previously thought to be rare and recessive. We demonstrate that disease manifests in both heterozygotes and homozygotes, indicating a common collagen disorder impacting up to 2% of individuals of Puerto Rican ancestry, leading to a better understanding of the continuum of complex and Mendelian disease.

Diseases often run in families. These disease are frequently linked to changes in DNA that are passed down through generations. Close family members may share these disease-causing mutations; so may distant relatives who inherited the same mutation from a common ancestor long ago. Geneticists use a method called linkage mapping to trace a disease found in multiple members of a family over generations to genetic changes in a shared ancestor. This allows scientists to pinpoint the exact place in the genome the disease-causing mutation occurred. Using computer algorithms, scientists can apply the same technique to identify mutations that distant relatives inherited from a common ancestor.

Belbin et al. used this computational technique to identify a mutation that may cause unusually short stature or bone and joint problems in up to 2% of people of Puerto Rican descent. In the experiments, the genomes of about 32,000 New Yorkers who have volunteered to participate in the BioMe Biobank and their health records were used to search for genetic changes linked to extremely short stature. The search revealed that people who inherited two copies of this mutation from their parents were likely to be extremely short or to have bone and joint problems. People who inherited one copy had an increased likelihood of joint or bone problems.

This mutation affects a gene responsible for making a form of protein called collagen that is important for bone growth. The analysis suggests the mutation first arose in a Native American ancestor living in Puerto Rico around the time that European colonization began. The mutation had previously been linked to a disorder called Steel syndrome that was thought to be rare. Belbin et al. showed this condition is actually fairly common in people whose ancestors recently came from Puerto Rico, but may often go undiagnosed by their physicians. The experiments emphasize the importance of including diverse populations in genetic studies, as studies of people of predominantly European descent would likely have missed the link between this disease and mutation.

GBA Analysis in Next-Generation Era: Pitfalls, Challenges, and Possible Solutions

Mutations in the gene encoding the lysosomal enzyme acid β-glucosidase (GBA) are responsible for Gaucher disease and represent the main genetic risk factor for developing Parkinson disease. In past years, next-generation sequencing (NGS) technology has been applied for the molecular analysis of the GBA gene, both as a single gene or as part of gene panels. However, the presence of complex gene-pseudogene rearrangements, resulting from the presence of a highly homologous pseudogene (GBAP1) located downstream of the GBA gene, makes NGS analysis of GBA challenging. Therefore, adequate strategies should be adopted to avoid misdetection of GBA recombinant mutations. Here, we validated a strategy for the identification of GBA mutations using parallel massive sequencing and provide an overview of the major drawbacks encountered during GBA analysis by NGS. We implemented a NGS workflow, using a set of 38 patients with Gaucher disease carrying different GBA alleles identified previously by Sanger sequencing. As expected, the presence of the pseudogene significantly affected data output. However, the combination of specific procedures for the library preparation and data analysis resulted in maximal repeatability and reproducibility, and a robust performance with 97% sensitivity and 100% specificity. In conclusion, the pipeline described here represents a useful approach to deal with GBA sequencing using NGS technology.

Interactions between four gene polymorphisms and their association with patients with Parkinson's disease in a Chinese Han population

The four previously reported Parkinson's disease (PD)-related single-nucleotide polymorphisms (SNPs) - rs1775143, rs823114, rs2071746 and rs62063857 - have rarely been studied in Chinese Han populations. To examine the association between these SNPs and PD, we conducted a case-control study of 158 patients with PD and 210 controls. All participants were Chinese Han from Northern China. With covariate adjustment for clinical characteristics, logistic regression analysis revealed no differences in genotype or allele frequencies for the four SNPs. Stratified by age of disease onset, sex, smoking status, duration of disease, baseline UPDRS, Hoehn-Yahr Stage, PD subtypes, scores of Hamilton anxiety scale, Hamilton depression scale and activity of daily living, all of the p values did not remain significant after Bonferroni correction. However, the haplotype rs1775143T-rs823114G-rs2071746T-rs62063857A was associated with increased risk of developing PD (p = 0.003, OR = 456.88, 95% CI: 27.40-7619.75) in our case-control sample set. The haplotype rs1775143T-rs823114G-rs2071746T was also associated with increased risk of developing PD (p = 0.003, OR = 338.43, 95% CI: 20.68-5538.27). Although the haplotype rs1775143T-rs823114G-rs62063857A was associated with increased risk of PD (p = 0.03), the 95% CI was 0.993-22.469. Our data demonstrate that although specific SNPs were not related with PD patients, certain haplotypes were associated with increased risk for PD in the Chinese Han population. These results provide further evidence that the etiology of PD is multifactorial, although the underling mechanism needs further study.

A fast and accurate method for detection of IBD shared haplotypes in genome-wide SNP data

Identical by descent (IBD) segments are used to understand a number of fundamental issues in genetics. IBD segments are typically detected using long stretches of identical alleles between haplotypes in phased, whole-genome SNP data. Phase or SNP call errors in genomic data can degrade accuracy of IBD detection and lead to false-positive/negative calls and to under/overextension of true IBD segments. Furthermore, the number of comparisons increases quadratically with sample size, requiring high computational efficiency. We developed a new IBD segment detection program, FISHR (Find IBD Shared Haplotypes Rapidly), in an attempt to accurately detect IBD segments and to better estimate their endpoints using an algorithm that is fast enough to be deployed on very large whole-genome SNP data sets. We compared the performance of FISHR to three leading IBD segment detection programs: GERMLINE, refined IBD, and HaploScore. Using simulated and real genomic sequence data, we show that FISHR is slightly more accurate than all programs at detecting long (>3 cm) IBD segments but slightly less accurate than refined IBD at detecting short (~1 cm) IBD segments. More centrally, FISHR outperforms all programs in determining the true endpoints of IBD segments, which is crucial for several applications of IBD information. FISHR takes two to three times longer than GERMLINE to run, whereas both GERMLINE and FISHR were orders of magnitude faster than refined IBD and HaploScore. Overall, FISHR provides accurate IBD detection in unrelated individuals and is computationally efficient enough to be utilized on large SNP data sets >60 000 individuals.

LRRK2 but not ATG16L1 is associated with Paneth cell defect in Japanese Crohn's disease patients

BACKGROUND. Morphological patterns of Paneth cells are a prognostic biomarker in Western Crohn's disease (CD) patients, and are associated with autophagy-associated ATG16L1 and NOD2 variants. We hypothesized that genetic determinants of Paneth cell phenotype in other ethnic CD cohorts are distinct but also involved in autophagy. METHODS. We performed a hypothesis-driven analysis of 56 single nucleotide polymorphisms (SNPs) associated with CD susceptibility or known to affect Paneth cell function in 110 Japanese CD patients who underwent ileal resection. We subsequently performed a genome-wide association analysis. Paneth cell phenotype was determined by defensin-5 immunofluorescence. Selected genotype-Paneth cell defect correlations were compared to a Western CD cohort (n = 164). RESULTS. The average percentage of abnormal Paneth cells in Japanese CD was similar to Western CD (P = 0.87), and abnormal Paneth cell phenotype was also associated with early recurrence (P = 0.013). In contrast to Western CD, ATG16L1 T300A was not associated with Paneth cell defect in Japanese CD (P = 0.20). Among the 56 selected SNPs, only LRRK2 M2397T showed significant association with Paneth cell defect (P = 3.62 × 10^-4), whereas in the Western CD cohort it was not (P = 0.76). Pathway analysis of LRRK2 and other candidate genes with P less than 5 × 10^-4 showed connections with known CD susceptibility genes and links to autophagy and TNF-α networks. CONCLUSIONS. We found dichotomous effects of ATG16L1 and LRRK2 on Paneth cell defect between Japanese and Western CD. Genes affecting Paneth cell phenotype in Japanese CD were also associated with autophagy. Paneth cell phenotype also predicted prognosis in Japanese CD. FUNDING. Helmsley Charitable Trust, Doris Duke Foundation (grant 2014103), Japan Society for the Promotion of Science (KAKENHI grants JP15H04805 and JP15K15284), Crohn's and Colitis Foundation grant 274415, NIH (grants 1R56DK095820, K01DK109081, and UL1 TR000448).

Genetic Determinants of Parkinson's Disease: Can They Help to Stratify the Patients Based on the Underlying Molecular Defect?

Parkinson's disease (PD) is a sporadic progressive neurodegenerative brain disorder with a relatively strong genetic background. We have reviewed the current literature about the genetic factors that could be indicative of pathophysiological pathways of PD and their applications in everyday clinical practice. Information on novel risk genes is coming from several genome-wide association studies (GWASs) and their meta-analyses. GWASs that have been performed so far enabled the identification of 24 loci as PD risk factors. These loci take part in numerous cellular processes that may contribute to PD pathology: protein aggregation, protein, and membrane trafficking, lysosomal autophagy, immune response, synaptic function, endocytosis, inflammation, and metabolic pathways are among the most important ones. The identified single nucleotide polymorphisms are usually located in the non-coding regions and their functionality remains to be determined, although they presumably influence gene expression. It is important to be aware of a very low contribution of a single genetic risk factor to PD development; therefore, novel prognostic indices need to account for the cumulative nature of genetic risk factors. A better understanding of PD pathophysiology and its genetic background will help to elucidate the underlying pathological processes. Such knowledge may help physicians to recognize subjects with the highest risk for the development of PD, and provide an opportunity for the identification of novel potential targets for neuroprotective treatment. Moreover, it may enable stratification of the PD patients according to their genetic fingerprint to properly personalize their treatment as well as supportive measures.

An assessment of the frequency of mutations in the GBA and VPS35 genes in Hungarian patients with sporadic Parkinson's disease

Parkinson's disease (PD) is the second most common neurodegenerative disorder, with cases of either familial or sporadic origin. Several polymorphisms in a number of genes have been proved to have an important role in the development of PD. Particular attention has recently been paid to genes of the glucocerebrosidase (GBA) and the vacuolar protein sorting-associated protein 35 (VPS35). In this study, the three most common mutations (L444P, N370S and R120W) of the GBA gene and the D620N mutation of the VPS35 gene were examined in 124 Hungarian patients diagnosed with sporadic PD (SPD) and 122 control subjects. The frequency of the L444P mutation of the GBA gene proved to be higher in the PD patients (2.4%) than in the controls (0%), although the difference was not statistically significant. All the patients who carried the mutant allele were in the early-onset PD (EOPD) group. However, neither the R120W nor the N370S variant of the GBA gene nor D620N mutation of the VPS35 gene were detected among the PD cases or the controls. Even though these results suggest that the studied mutations are quite rare in SPD patients, the most frequent L444P mutation of the GBA gene may be associated with the development of EOPD in the Hungarian population.

The Alzheimer disease BIN1 locus as a modifier of GBA-associated Parkinson disease

GBA mutations are among the most common genetic risk factors for Parkinson disease (PD) worldwide. We aimed to identify genetic modifiers of the age at onset (AAO) in GBA-associated PD. The study included a genome-wide discovery phase, including a cohort of 79 patients with the GBA p.N370S mutation, and candidate validation and replication analyses of 8 SNPs in patients with mild (n = 113) and severe (n = 41) GBA mutations. Genotyping was performed using the Affymetrix human SNP 6.0 array and TaqMan assays. In the genome-wide phase, none of the SNPs passed the genome-wide significance threshold. Eight SNPs were selected for further analysis from the top hits. In all GBA-associated PD patients (n = 153), the BIN1 rs13403026 minor allele was associated with an older AAO (12.4 ± 5.9 years later, p = 0.0001), compared to patients homozygous for the major allele. Furthermore, the AAO was 10.7 ± 6.8 years later in patients with mild GBA mutations, (p = 0.005, validation group), and 17.1 ± 2.5 years later in patients with severe GBA mutations (p = 0.01, replication). Our results suggest that alterations in the BIN1 locus, previously associated with Alzheimer disease, may modify the AAO of GBA-associated PD. More studies in other populations are required to examine the role of BIN1-related variants in GBA-associated PD.

Gaucher-related synucleinopathies: the examination of sporadic neurodegeneration from a rare (disease) angle

Gaucher disease, the most common lysosomal storage disease, is caused by a recessively inherited deficiency in glucocerebrosidase and subsequent accumulation of toxic lipid substrates. Heterozygous mutations in the lysosomal glucocerebrosidase gene (GBA1) have recently been recognized as the highest genetic risk factor for the development of α-synuclein aggregation disorders ("synucleinopathies"), including Parkinson's disease (PD) and dementia with Lewy bodies (DLB). Despite the wealth of experimental, clinical and genetic evidence that supports the association between mutant genotypes and synucleinopathy risk, the precise mechanisms by which GBA1 mutations lead to PD and DLB remain unclear. Decreased glucocerebrosidase activity has been demonstrated to promote α-synuclein misprocessing. Furthermore, aberrant α-synuclein species have been reported to downregulate glucocerebrosidase activity, which further contributes to disease progression. In this review, we summarize the recent findings that highlight the complexity of this pathogenetic link and how several pathways that connect glucocerebrosidase insufficiency with α-synuclein misprocessing have emerged as potential therapeutic targets. From a translational perspective, we discuss how various therapeutic approaches to lysosomal dysfunction have been explored for the treatment of GBA1-related synucleinopathies, and potentially, for non-GBA1-associated neurodegenerative diseases. In summary, the link between GBA1 and synucleinopathies has become the paradigm of how the study of a rare lysosomal disease can transform the understanding of the etiopathology, and hopefully the treatment, of a more prevalent and multifactorial disorder.