Polygenic Risk Scores Validated in Patient-Derived Cells Stratify for Mitochondrial Subtypes of Parkinson's Disease.

OBJECTIVE: The aim of our study is to better understand the genetic architecture and pathological mechanisms underlying neurodegeneration in idiopathic Parkinson's disease (iPD). We hypothesized that a fraction of iPD patients may harbor a combination of common variants in nuclear-encoded mitochondrial genes ultimately resulting in neurodegeneration. METHODS: We used mitochondria-specific polygenic risk scores (mitoPRSs) and created pathway-specific mitoPRSs using genotype data from different iPD case-control datasets worldwide, including the Luxembourg Parkinson's Study (412 iPD patients and 576 healthy controls) and COURAGE-PD cohorts (7,270 iPD cases and 6,819 healthy controls). Cellular models from individuals stratified according to the most significant mitoPRS were subsequently used to characterize different aspects of mitochondrial function. RESULTS: Common variants in genes regulating Oxidative Phosphorylation (OXPHOS-PRS) were significantly associated with a higher PD risk in independent cohorts (Luxembourg Parkinson's Study odds ratio, OR = 1.31[1.14-1.50], p-value = 5.4e-04; COURAGE-PD OR = 1.23[1.18-1.27], p-value = 1.5e-29). Functional analyses in fibroblasts and induced pluripotent stem cells-derived neuronal progenitors revealed significant differences in mitochondrial respiration between iPD patients with high or low OXPHOS-PRS (p-values < 0.05). Clinically, iPD patients with high OXPHOS-PRS have a significantly earlier age at disease onset compared to low-risk patients (false discovery rate [FDR]-adj p-value = 0.015), similar to prototypic monogenic forms of PD. Finally, iPD patients with high OXPHOS-PRS responded more effectively to treatment with mitochondrially active ursodeoxycholic acid. INTERPRETATION: OXPHOS-PRS may provide a precision medicine tool to stratify iPD patients into a pathogenic subgroup genetically defined by specific mitochondrial impairment, making these individuals eligible for future intelligent clinical trial designs. ANN NEUROL 2024;96:133-149.

binny: an automated binning algorithm to recover high-quality genomes from complex metagenomic datasets.

The reconstruction of genomes is a critical step in genome-resolved metagenomics and for multi-omic data integration from microbial communities. Here, we present binny, a binning tool that produces high-quality metagenome-assembled genomes (MAG) from both contiguous and highly fragmented genomes. Based on established metrics, binny outperforms or is highly competitive with commonly used and state-of-the-art binning methods and finds unique genomes that could not be detected by other methods. binny uses k-mer-composition and coverage by metagenomic reads for iterative, nonlinear dimension reduction of genomic signatures as well as subsequent automated contig clustering with cluster assessment using lineage-specific marker gene sets. When compared with seven widely used binning algorithms, binny provides substantial amounts of uniquely identified MAGs and almost always recovers the most near-complete ($\gt 95\%$ pure, $\gt 90\%$ complete) and high-quality ($\gt 90\%$ pure, $\gt 70\%$ complete) genomes from simulated datasets from the Critical Assessment of Metagenome Interpretation initiative, as well as substantially more high-quality draft genomes, as defined by the Minimum Information about a Metagenome-Assembled Genome standard, from a real-world benchmark comprised of metagenomes from various environments than any other tested method.

CNV-ClinViewer: enhancing the clinical interpretation of large copy-number variants online.

MOTIVATION: Pathogenic copy-number variants (CNVs) can cause a heterogeneous spectrum of rare and severe disorders. However, most CNVs are benign and are part of natural variation in human genomes. CNV pathogenicity classification, genotype-phenotype analyses, and therapeutic target identification are challenging and time-consuming tasks that require the integration and analysis of information from multiple scattered sources by experts. RESULTS: Here, we introduce the CNV-ClinViewer, an open-source web application for clinical evaluation and visual exploration of CNVs. The application enables real-time interactive exploration of large CNV datasets in a user-friendly designed interface and facilitates semi-automated clinical CNV interpretation following the ACMG guidelines by integrating the ClassifCNV tool. In combination with clinical judgment, the application enables clinicians and researchers to formulate novel hypotheses and guide their decision-making process. Subsequently, the CNV-ClinViewer enhances for clinical investigators' patient care and for basic scientists' translational genomic research. AVAILABILITY AND IMPLEMENTATION: The web application is freely available at https://cnv-ClinViewer.broadinstitute.org and the open-source code can be found at https://github.com/LalResearchGroup/CNV-clinviewer.

Dissecting genetics of spectrum of epilepsies with eyelid myoclonia by exome sequencing.

OBJECTIVE: Epilepsy with eyelid myoclonia (EEM) spectrum is a generalized form of epilepsy characterized by eyelid myoclonia with or without absences, eye closure-induced seizures with electroencephalographic paroxysms, and photosensitivity. Based on the specific clinical features, age at onset, and familial occurrence, a genetic cause has been postulated. Pathogenic variants in CHD2, SYNGAP1, NEXMIF, RORB, and GABRA1 have been reported in individuals with photosensitivity and eyelid myoclonia, but whether other genes are also involved, or a single gene is uniquely linked with EEM, or its subtypes, is not yet known. We aimed to dissect the genetic etiology of EEM. METHODS: We studied a cohort of 105 individuals by using whole exome sequencing. Individuals were divided into two groups: EEM- (isolated EEM) and EEM+ (EEM accompanied by intellectual disability [ID] or any other neurodevelopmental/psychiatric disorder). RESULTS: We identified nine variants classified as pathogenic/likely pathogenic in the entire cohort (8.57%); among these, eight (five in CHD2, one in NEXMIF, one in SYNGAP1, and one in TRIM8) were found in the EEM+ subcohort (28.57%). Only one variant (IFIH1) was found in the EEM- subcohort (1.29%); however, because the phenotype of the proband did not fit with published data, additional evidence is needed before considering IFIH1 variants and EEM- an established association. Burden analysis did not identify any single burdened gene or gene set. SIGNIFICANCE: Our results suggest that for EEM, as for many other epilepsies, the identification of a genetic cause is more likely with comorbid ID and/or other neurodevelopmental disorders. Pathogenic variants were mostly found in CHD2, and the association of CHD2 with EEM+ can now be considered a reasonable gene-disease association. We provide further evidence to strengthen the association of EEM+ with NEXMIF and SYNGAP1. Possible new associations between EEM+ and TRIM8, and EEM- and IFIH1, are also reported. Although we provide robust evidence for gene variants associated with EEM+, the core genetic etiology of EEM- remains to be elucidated.

Delineation of functionally essential protein regions for 242 neurodevelopmental genes.

Neurodevelopmental disorders (NDDs), including severe paediatric epilepsy, autism and intellectual disabilities are heterogeneous conditions in which clinical genetic testing can often identify a pathogenic variant. For many of them, genetic therapies will be tested in this or the coming years in clinical trials. In contrast to first-generation symptomatic treatments, the new disease-modifying precision medicines require a genetic test-informed diagnosis before a patient can be enrolled in a clinical trial. However, even in 2022, most identified genetic variants in NDD genes are 'variants of uncertain significance'. To safely enrol patients in precision medicine clinical trials, it is important to increase our knowledge about which regions in NDD-associated proteins can 'tolerate' missense variants and which ones are 'essential' and will cause a NDD when mutated. In addition, knowledge about functionally indispensable regions in the 3D structure context of proteins can also provide insights into the molecular mechanisms of disease variants. We developed a novel consensus approach that overlays evolutionary, and population based genomic scores to identify 3D essential sites (Essential3D) on protein structures. After extensive benchmarking of AlphaFold predicted and experimentally solved protein structures, we generated the currently largest expert curated protein structure set for 242 NDDs and identified 14 377 Essential3D sites across 189 gene disorders associated proteins. We demonstrate that the consensus annotation of Essential3D sites improves prioritization of disease mutations over single annotations. The identified Essential3D sites were enriched for functional features such as intermembrane regions or active sites and discovered key inter-molecule interactions in protein complexes that were otherwise not annotated. Using the currently largest autism, developmental disorders, and epilepsies exome sequencing studies including >360 000 NDD patients and population controls, we found that missense variants at Essential3D sites are 8-fold enriched in patients. In summary, we developed a comprehensive protein structure set for 242 NDDs and identified 14 377 Essential3D sites in these. All data are available at https://es-ndd.broadinstitute.org for interactive visual inspection to enhance variant interpretation and development of mechanistic hypotheses for 242 NDDs genes. The provided resources will enhance clinical variant interpretation and in silico drug target development for NDD-associated genes and encoded proteins.

Conserved patterns across ion channels correlate with variant pathogenicity and clinical phenotypes.

Clinically identified genetic variants in ion channels can be benign or cause disease by increasing or decreasing the protein function. As a consequence, therapeutic decision-making is challenging without molecular testing of each variant. Our biophysical knowledge of ion-channel structures and function is just emerging, and it is currently not well understood which amino acid residues cause disease when mutated. We sought to systematically identify biological properties associated with variant pathogenicity across all major voltage and ligand-gated ion-channel families. We collected and curated 3049 pathogenic variants from hundreds of neurodevelopmental and other disorders and 12 546 population variants for 30 ion channel or channel subunits for which a high-quality protein structure was available. Using a wide range of bioinformatics approaches, we computed 163 structural features and tested them for pathogenic variant enrichment. We developed a novel 3D spatial distance scoring approach that enables comparisons of pathogenic and population variant distribution across protein structures. We discovered and independently replicated that several pore residue properties and proximity to the pore axis were most significantly enriched for pathogenic variants compared to population variants. Using our 3D scoring approach, we showed that the strongest pathogenic variant enrichment was observed for pore-lining residues and alpha-helix residues within 5Å distance from the pore axis centre and not involved in gating. Within the subset of residues located at the pore, the hydrophobicity of the pore was the feature most strongly associated with variant pathogenicity. We also found an association between the identified properties and both clinical phenotypes and functional in vitro assays for voltage-gated sodium channels (SCN1A, SCN2A, SCN8A) and N-methyl-D-aspartate receptor (GRIN1, GRIN2A, GRIN2B) encoding genes. In an independent expert-curated dataset of 1422 neurodevelopmental disorder pathogenic patient variants and 679 electrophysiological experiments, we show that pore axis distance is associated with seizure age of onset and cognitive performance as well as differential gain versus loss-of-channel function. In summary, we identified biological properties associated with ion-channel malfunction and show that these are correlated with in vitro functional readouts and clinical phenotypes in patients with neurodevelopmental disorders. Our results suggest that clinical decision support algorithms that predict variant pathogenicity and function are feasible in the future.

Mitochondrial DNA heteroplasmy distinguishes disease manifestation in PINK1/PRKN-linked Parkinson's disease.

Biallelic mutations in PINK1/PRKN cause recessive Parkinson's disease. Given the established role of PINK1/Parkin in regulating mitochondrial dynamics, we explored mitochondrial DNA integrity and inflammation as disease modifiers in carriers of mutations in these genes. Mitochondrial DNA integrity was investigated in a large collection of biallelic (n = 84) and monoallelic (n = 170) carriers of PINK1/PRKN mutations, idiopathic Parkinson's disease patients (n = 67) and controls (n = 90). In addition, we studied global gene expression and serum cytokine levels in a subset. Affected and unaffected PINK1/PRKN monoallelic mutation carriers can be distinguished by heteroplasmic mitochondrial DNA variant load (area under the curve = 0.83, CI 0.74-0.93). Biallelic PINK1/PRKN mutation carriers harbour more heteroplasmic mitochondrial DNA variants in blood (P = 0.0006, Z = 3.63) compared to monoallelic mutation carriers. This enrichment was confirmed in induced pluripotent stem cell-derived (controls, n = 3; biallelic PRKN mutation carriers, n = 4) and post-mortem (control, n = 1; biallelic PRKN mutation carrier, n = 1) midbrain neurons. Last, the heteroplasmic mitochondrial DNA variant load correlated with IL6 levels in PINK1/PRKN mutation carriers (r = 0.57, P = 0.0074). PINK1/PRKN mutations predispose individuals to mitochondrial DNA variant accumulation in a dose- and disease-dependent manner.

SLC6A1 variant pathogenicity, molecular function and phenotype: a genetic and clinical analysis.

Genetic variants in the SLC6A1 gene can cause a broad phenotypic disease spectrum by altering the protein function. Thus, systematically curated clinically relevant genotype-phenotype associations are needed to understand the disease mechanism and improve therapeutic decision-making. We aggregated genetic and clinical data from 172 individuals with likely pathogenic/pathogenic (lp/p) SLC6A1 variants and functional data for 184 variants (14.1% lp/p). Clinical and functional data were available for a subset of 126 individuals. We explored the potential associations of variant positions on the GAT1 3D structure with variant pathogenicity, altered molecular function and phenotype severity using bioinformatic approaches. The GAT1 transmembrane domains 1, 6 and extracellular loop 4 (EL4) were enriched for patient over population variants. Across functionally tested missense variants (n = 156), the spatial proximity from the ligand was associated with loss-of-function in the GAT1 transporter activity. For variants with complete loss of in vitro GABA uptake, we found a 4.6-fold enrichment in patients having severe disease versus non-severe disease (P = 2.9 × 10-3, 95% confidence interval: 1.5-15.3). In summary, we delineated associations between the 3D structure and variant pathogenicity, variant function and phenotype in SLC6A1-related disorders. This knowledge supports biology-informed variant interpretation and research on GAT1 function. All our data can be interactively explored in the SLC6A1 portal (https://slc6a1-portal.broadinstitute.org/).

Identification of pathogenic variant enriched regions across genes and gene families.

Missense variant interpretation is challenging. Essential regions for protein function are conserved among gene-family members, and genetic variants within these regions are potentially more likely to confer risk to disease. Here, we generated 2871 gene-family protein sequence alignments involving 9990 genes and performed missense variant burden analyses to identify novel essential protein regions. We mapped 2,219,811 variants from the general population into these alignments and compared their distribution with 76,153 missense variants from patients. With this gene-family approach, we identified 465 regions enriched for patient variants spanning 41,463 amino acids in 1252 genes. As a comparison, by testing the same genes individually, we identified fewer patient variant enriched regions, involving only 2639 amino acids and 215 genes. Next, we selected de novo variants from 6753 patients with neurodevelopmental disorders and 1911 unaffected siblings and observed an 8.33-fold enrichment of patient variants in our identified regions (95% C.I. = 3.90-Inf, P-value = 2.72 × 10-11). By using the complete ClinVar variant set, we found that missense variants inside the identified regions are 106-fold more likely to be classified as pathogenic in comparison to benign classification (OR = 106.15, 95% C.I = 70.66-Inf, P-value < 2.2 × 10-16). All pathogenic variant enriched regions (PERs) identified are available online through "PER viewer," a user-friendly online platform for interactive data mining, visualization, and download. In summary, our gene-family burden analysis approach identified novel PERs in protein sequences. This annotation can empower variant interpretation.

Comparison of two protocols for the generation of iPSC-derived human astrocytes.

BACKGROUND: Astrocytes have recently gained attention as key contributors to the pathogenesis of neurodegenerative disorders including Parkinson's disease. To investigate human astrocytes in vitro, numerous differentiation protocols have been developed. However, the properties of the resulting glia are inconsistent, which complicates the selection of an appropriate method for a given research question. Thus, we compared two approaches for the generation of iPSC-derived astrocytes. We phenotyped glia that were obtained employing a widely used long, serum-free ("LSF") method against an in-house established short, serum-containing ("SSC") protocol which allows for the generation of astrocytes and midbrain neurons from the same precursor cells. RESULTS: We employed high-content confocal imaging and RNA sequencing to characterize the cultures. The astrocytes generated with the LSF or SSC protocols differed considerably in their properties: while the former cells were more labor-intense in their generation (5 vs 2 months), they were also more mature. This notion was strengthened by data resulting from cell type deconvolution analysis that was applied to bulk transcriptomes from the cultures to assess their similarity with human postmortem astrocytes. CONCLUSIONS: Overall, our analyses highlight the need to consider the advantages and disadvantages of a given differentiation protocol, when designing functional or drug discovery studies involving iPSC-derived astrocytes.

Functional meta-omics provide critical insights into long- and short-read assemblies.

Real-world evaluations of metagenomic reconstructions are challenged by distinguishing reconstruction artifacts from genes and proteins present in situ. Here, we evaluate short-read-only, long-read-only and hybrid assembly approaches on four different metagenomic samples of varying complexity. We demonstrate how different assembly approaches affect gene and protein inference, which is particularly relevant for downstream functional analyses. For a human gut microbiome sample, we use complementary metatranscriptomic and metaproteomic data to assess the metagenomic data-based protein predictions. Our findings pave the way for critical assessments of metagenomic reconstructions. We propose a reference-independent solution, which exploits the synergistic effects of multi-omic data integration for the in situ study of microbiomes using long-read sequencing data.

Investigation of Shared Genetic Risk Factors Between Parkinson's Disease and Cancers.

BACKGROUND: Epidemiological studies that examined the association between Parkinson's disease (PD) and cancers led to inconsistent results, but they face a number of methodological difficulties. OBJECTIVE: We used results from genome-wide association studies (GWASs) to study the genetic correlation between PD and different cancers to identify common genetic risk factors. METHODS: We used individual data for participants of European ancestry from the Courage-PD (Comprehensive Unbiased Risk Factor Assessment for Genetics and Environment in Parkinson's Disease; PD, N = 16,519) and EPITHYR (differentiated thyroid cancer, N = 3527) consortia and summary statistics of GWASs from iPDGC (International Parkinson Disease Genomics Consortium; PD, N = 482,730), Melanoma Meta-Analysis Consortium (MMAC), Breast Cancer Association Consortium (breast cancer), the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (prostate cancer), International Lung Cancer Consortium (lung cancer), and Ovarian Cancer Association Consortium (ovarian cancer) (N comprised between 36,017 and 228,951 for cancer GWASs). We estimated the genetic correlation between PD and cancers using linkage disequilibrium score regression. We studied the association between PD and polymorphisms associated with cancers, and vice versa, using cross-phenotypes polygenic risk score (PRS) analyses. RESULTS: We confirmed a previously reported positive genetic correlation of PD with melanoma (Gcorr = 0.16 [0.04; 0.28]) and reported an additional significant positive correlation of PD with prostate cancer (Gcorr = 0.11 [0.03; 0.19]). There was a significant inverse association between the PRS for ovarian cancer and PD (odds ratio [OR] = 0.89 [0.84; 0.94]). Conversely, the PRS of PD was positively associated with breast cancer (OR = 1.08 [1.06; 1.10]) and inversely associated with ovarian cancer (OR = 0.95 [0.91; 0.99]). The association between PD and ovarian cancer was mostly driven by rs183211 located in an intron of the NSF gene (17q21.31). CONCLUSIONS: We show evidence in favor of a contribution of pleiotropic genes to the association between PD and specific cancers. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Single-cell sequencing of human midbrain reveals glial activation and a Parkinson-specific neuronal state.

Idiopathic Parkinson's disease is characterized by a progressive loss of dopaminergic neurons, but the exact disease aetiology remains largely unknown. To date, Parkinson's disease research has mainly focused on nigral dopaminergic neurons, although recent studies suggest disease-related changes also in non-neuronal cells and in midbrain regions beyond the substantia nigra. While there is some evidence for glial involvement in Parkinson's disease, the molecular mechanisms remain poorly understood. The aim of this study was to characterize the contribution of all cell types of the midbrain to Parkinson's disease pathology by single-nuclei RNA sequencing and to assess the cell type-specific risk for Parkinson's disease using the latest genome-wide association study. We profiled >41 000 single-nuclei transcriptomes of post-mortem midbrain from six idiopathic Parkinson's disease patients and five age-/sex-matched controls. To validate our findings in a spatial context, we utilized immunolabelling of the same tissues. Moreover, we analysed Parkinson's disease-associated risk enrichment in genes with cell type-specific expression patterns. We discovered a neuronal cell cluster characterized by CADPS2 overexpression and low TH levels, which was exclusively present in idiopathic Parkinson's disease midbrains. Validation analyses in laser-microdissected neurons suggest that this cluster represents dysfunctional dopaminergic neurons. With regard to glial cells, we observed an increase in nigral microglia in Parkinson's disease patients. Moreover, nigral idiopathic Parkinson's disease microglia were more amoeboid, indicating an activated state. We also discovered a reduction in idiopathic Parkinson's disease oligodendrocyte numbers with the remaining cells being characterized by a stress-induced upregulation of S100B. Parkinson's disease risk variants were associated with glia- and neuron-specific gene expression patterns in idiopathic Parkinson's disease cases. Furthermore, astrocytes and microglia presented idiopathic Parkinson's disease-specific cell proliferation and dysregulation of genes related to unfolded protein response and cytokine signalling. While reactive patient astrocytes showed CD44 overexpression, idiopathic Parkinson's disease microglia revealed a pro-inflammatory trajectory characterized by elevated levels of IL1B, GPNMB and HSP90AA1. Taken together, we generated the first single-nuclei RNA sequencing dataset from the idiopathic Parkinson's disease midbrain, which highlights a disease-specific neuronal cell cluster as well as 'pan-glial' activation as a central mechanism in the pathology of the movement disorder. This finding warrants further research into inflammatory signalling and immunomodulatory treatments in Parkinson's disease.

Comprehensive characterization of amino acid positions in protein structures reveals molecular effect of missense variants.

Interpretation of the colossal number of genetic variants identified from sequencing applications is one of the major bottlenecks in clinical genetics, with the inference of the effect of amino acid-substituting missense variations on protein structure and function being especially challenging. Here we characterize the three-dimensional (3D) amino acid positions affected in pathogenic and population variants from 1,330 disease-associated genes using over 14,000 experimentally solved human protein structures. By measuring the statistical burden of variations (i.e., point mutations) from all genes on 40 3D protein features, accounting for the structural, chemical, and functional context of the variations' positions, we identify features that are generally associated with pathogenic and population missense variants. We then perform the same amino acid-level analysis individually for 24 protein functional classes, which reveals unique characteristics of the positions of the altered amino acids: We observe up to 46% divergence of the class-specific features from the general characteristics obtained by the analysis on all genes, which is consistent with the structural diversity of essential regions across different protein classes. We demonstrate that the function-specific 3D features of the variants match the readouts of mutagenesis experiments for BRCA1 and PTEN, and positively correlate with an independent set of clinically interpreted pathogenic and benign missense variants. Finally, we make our results available through a web server to foster accessibility and downstream research. Our findings represent a crucial step toward translational genetics, from highlighting the impact of mutations on protein structure to rationalizing the variants' pathogenicity in terms of the perturbed molecular mechanisms.

Benchmarking of univariate pleiotropy detection methods applied to epilepsy.

Pleiotropy is a widespread phenomenon that may increase insight into the etiology of biological and disease traits. Since genome-wide association studies frequently provide information on a single trait only, only univariate pleiotropy detection methods are applicable, with yet unknown comparative performance. Here, we compared five such methods with respect to their ability to detect pleiotropy, including meta-analysis, ASSET, conditional false discovery rate (cFDR), cross-phenotype Bayes (CPBayes), and pleiotropic analysis under the composite null hypothesis (PLACO), by performing extended computer simulations that varied the underlying etiological model for pleiotropy for a pair of traits, including the number of causal variants, degree of traits' overlap, effect sizes as well as trait prevalence, and varying sample sizes. Our results indicate that ASSET provides the best trade-off between power and protection against false positives. We then applied ASSET to a previously published International League Against Epilepsy (ILAE) consortium data set on complex epilepsies, comprising genetic generalized epilepsy and focal epilepsy cases and corresponding controls. We identified a novel candidate locus at 17q21.32 and confirmed locus 2q24.3, previously identified to act pleiotropically on both epilepsy subtypes by a mega-analysis. Functional annotation, tissue-specific expression, and regulatory function analysis as well as Bayesian colocalization analysis corroborated this result, rendering 17q21.32 a worthwhile candidate for follow-up studies on pleiotropy in epilepsies.

Breast and prostate cancer risk: The interplay of polygenic risk, rare pathogenic germline variants, and family history.

PURPOSE: We aimed to investigate to what extent polygenic risk scores (PRS), rare pathogenic germline variants (PVs), and family history jointly influence breast cancer and prostate cancer risk. METHODS: A total of 200,643 individuals from the UK Biobank were categorized as follows: (1) heterozygotes or nonheterozygotes for PVs in moderate to high-risk cancer genes, (2) PRS strata, and (3) with or without a family history of cancer. Multivariable logistic regression and Cox proportional hazards models were used to compute the odds ratio across groups and the cumulative incidence through life. RESULTS: Cumulative incidence by age 70 years among the nonheterozygotes across PRS strata ranged from 9% to 32% and from 9% to 35% for breast cancer and prostate cancer, respectively. Among the PV heterozygotes it ranged from 20% to 48% in moderate-risk genes and from 51% to 74% in high-risk genes for breast cancer, and it ranged from 30% to 59% in prostate cancer risk genes. Family history was always associated with an increased cancer odds ratio. CONCLUSION: PRS alone provides a meaningful risk gradient leading to a cancer risk stratification comparable to PVs in moderate risk genes, whereas acts as a risk modifier when considering high-risk genes. Including family history along with PV and PRS further improves cancer risk stratification.

Dairy Intake and Parkinson's Disease: A Mendelian Randomization Study.

BACKGROUND: Previous prospective studies highlighted dairy intake as a risk factor for Parkinson's disease (PD), particularly in men. It is unclear whether this association is causal or explained by reverse causation or confounding. OBJECTIVE: The aim is to examine the association between genetically predicted dairy intake and PD using two-sample Mendelian randomization (MR). METHODS: We genotyped a well-established instrumental variable for dairy intake located in the lactase gene (rs4988235) within the Courage-PD consortium (23 studies; 9823 patients and 8376 controls of European ancestry). RESULTS: Based on a dominant model, there was an association between genetic predisposition toward higher dairy intake and PD (odds ratio [OR] per one serving per day = 1.70, 95% confidence interval = 1.12-2.60, P = 0.013) that was restricted to men (OR = 2.50 [1.37-4.56], P = 0.003; P-difference with women = 0.029). CONCLUSIONS: Using MR, our findings provide further support for a causal relationship between dairy intake and higher PD risk, not biased by confounding or reverse causation. Further studies are needed to elucidate the underlying mechanisms. © 2022 International Parkinson and Movement Disorder Society.

The Interaction between HLA-DRB1 and Smoking in Parkinson's Disease Revisited.

BACKGROUND: Two studies that examined the interaction between HLA-DRB1 and smoking in Parkinson's disease (PD) yielded findings in opposite directions. OBJECTIVE: To perform a large-scale independent replication of the HLA-DRB1 × smoking interaction. METHODS: We genotyped 182 single nucleotide polymorphism (SNPs) associated with smoking initiation in 12 424 cases and 9480 controls to perform a Mendelian randomization (MR) analysis in strata defined by HLA-DRB1. RESULTS: At the amino acid level, a valine at position 11 (V11) in HLA-DRB1 displayed the strongest association with PD. MR showed an inverse association between genetically predicted smoking initiation and PD only in absence of V11 (odds ratio, 0.74, 95% confidence interval, 0.59-0.93, PInteraction  = 0.028). In silico predictions of the influence of V11 and smoking-induced modifications of α-synuclein on binding affinity showed findings consistent with this interaction pattern. CONCLUSIONS: Despite being one of the most robust findings in PD research, the mechanisms underlying the inverse association between smoking and PD remain unknown. Our findings may help better understand this association. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Association of ultra-rare coding variants with genetic generalized epilepsy: A case-control whole exome sequencing study.

OBJECTIVE: We aimed to identify genes associated with genetic generalized epilepsy (GGE) by combining large cohorts enriched with individuals with a positive family history. Secondarily, we set out to compare the association of genes independently with familial and sporadic GGE. METHODS: We performed a case-control whole exome sequencing study in unrelated individuals of European descent diagnosed with GGE (previously recruited and sequenced through multiple international collaborations) and ancestry-matched controls. The association of ultra-rare variants (URVs; in 18 834 protein-coding genes) with epilepsy was examined in 1928 individuals with GGE (vs. 8578 controls), then separately in 945 individuals with familial GGE (vs. 8626 controls), and finally in 1005 individuals with sporadic GGE (vs. 8621 controls). We additionally examined the association of URVs with familial and sporadic GGE in two gene sets important for inhibitory signaling (19 genes encoding γ-aminobutyric acid type A [GABAA ] receptors, 113 genes representing the GABAergic pathway). RESULTS: GABRG2 was associated with GGE (p = 1.8 × 10-5 ), approaching study-wide significance in familial GGE (p = 3.0 × 10-6 ), whereas no gene approached a significant association with sporadic GGE. Deleterious URVs in the most intolerant subgenic regions in genes encoding GABAA receptors were associated with familial GGE (odds ratio [OR] = 3.9, 95% confidence interval [CI] = 1.9-7.8, false discovery rate [FDR]-adjusted p = .0024), whereas their association with sporadic GGE had marginally lower odds (OR = 3.1, 95% CI = 1.3-6.7, FDR-adjusted p = .022). URVs in GABAergic pathway genes were associated with familial GGE (OR = 1.8, 95% CI = 1.3-2.5, FDR-adjusted p = .0024) but not with sporadic GGE (OR = 1.3, 95% CI = .9-1.9, FDR-adjusted p = .19). SIGNIFICANCE: URVs in GABRG2 are likely an important risk factor for familial GGE. The association of gene sets of GABAergic signaling with familial GGE is more prominent than with sporadic GGE.

Auditory cortex modelled as a dynamical network of oscillators: understanding event-related fields and their adaptation.

Adaptation, the reduction of neuronal responses by repetitive stimulation, is a ubiquitous feature of auditory cortex (AC). It is not clear what causes adaptation, but short-term synaptic depression (STSD) is a potential candidate for the underlying mechanism. In such a case, adaptation can be directly linked with the way AC produces context-sensitive responses such as mismatch negativity and stimulus-specific adaptation observed on the single-unit level. We examined this hypothesis via a computational model based on AC anatomy, which includes serially connected core, belt, and parabelt areas. The model replicates the event-related field (ERF) of the magnetoencephalogram as well as ERF adaptation. The model dynamics are described by excitatory and inhibitory state variables of cell populations, with the excitatory connections modulated by STSD. We analysed the system dynamics by linearising the firing rates and solving the STSD equation using time-scale separation. This allows for characterisation of AC dynamics as a superposition of damped harmonic oscillators, so-called normal modes. We show that repetition suppression of the N1m is due to a mixture of causes, with stimulus repetition modifying both the amplitudes and the frequencies of the normal modes. In this view, adaptation results from a complete reorganisation of AC dynamics rather than a reduction of activity in discrete sources. Further, both the network structure and the balance between excitation and inhibition contribute significantly to the rate with which AC recovers from adaptation. This lifetime of adaptation is longer in the belt and parabelt than in the core area, despite the time constants of STSD being spatially homogeneous. Finally, we critically evaluate the use of a single exponential function to describe recovery from adaptation.