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Parkinson's disease is a complex neurodegenerative disorder for which both rare and common genetic variants contribute to disease risk, onset, and progression. Mutations in more than 20 genes have been associated with the disease, most of which are highly penetrant and often cause early onset or atypical symptoms. Although our understanding of the genetic basis of Parkinson's disease has advanced considerably, much remains to be done. Further disease-related common genetic variability remains to be identified and the work in identifying rare risk alleles has only just begun. To date, genome-wide association studies have identified 90 independent risk-associated variants. However, most of them have been identified in patients of European ancestry and we know relatively little of the genetics of Parkinson's disease in other populations. We have a limited understanding of the biological functions of the risk alleles that have been identified, although Parkinson's disease risk variants appear to be in close proximity to known Parkinson's disease genes and lysosomal-related genes. In the past decade, multiple efforts have been made to investigate the genetic architecture of Parkinson's disease, and emerging technologies, such as machine learning, single-cell RNA sequencing, and high-throughput screens, will improve our understanding of genetic risk.

There has been tremendous progress toward understanding the genetic basis of Parkinson’s disease and related movement disorders. We summarize the genetic, clinical and pathological findings of autosomal dominant disease linked to mutations in SNCA , LRRK2 , ATXN2 , ATXN3 , MAPT, GCH1, DCTN1 and VPS35 . We then discuss the identification of mutations in PARK2 , PARK7 , PINK1 , ATP13A2 , FBXO7 , PANK2 and PLA2G6 genes. In particular we discuss the clinical and pathological characterization of these forms of disease, where neuropathology has been important in the likely coalescence of pathways highly relevant to typical PD. In addition to the identification of the causes of monogenic forms of PD, significant progress has been made in defining genetic risk loci for PD; we discuss these here, including both risk variants at LRRK2 and GBA , in addition to discussing the results of recent genome-wide association studies and their implications for PD. Finally, we discuss the likely path of genetic discovery in PD over the coming period and the implications of these findings from a clinical and etiological perspective.

Genomewide association studies have uncovered many genetic variants that confer susceptibility to disease. This article describes the genomewide association study and new approaches that may address some of its limitations. Genomewide association studies have uncovered many genetic variants that confer susceptibility to disease. This article describes the genomewide association study and new approaches that may address some of its limitations. For 20 years, genetic linkage combined with positional cloning has offered a rational and increasingly straightforward route to finding gene mutations that lead to monogenic disease, such as cystic fibrosis and Huntington's disease (see the Glossary). With a few important exceptions, these searches have led to mutations that alter the amino acid sequence of a protein and that enormously increase the risk of disease. During the past few years, genomewide association studies have identified a large number of robust associations between specific chromosomal loci and complex human disease, such as type 2 diabetes and rheumatoid arthritis 1 (Figure 1). This approach . . .

Robert Graham and colleagues carried out a GWAS meta-analysis for Parkinson's disease (PD) and report 17 new risk loci. Their analyses support a key role for autophagy and lysosomal biology in PD risk. Common variant genome-wide association studies (GWASs) have, to date, identified >24 risk loci for Parkinson's disease (PD). To discover additional loci, we carried out a GWAS comparing 6,476 PD cases with 302,042 controls, followed by a meta-analysis with a recent study of over 13,000 PD cases and 95,000 controls at 9,830 overlapping variants. We then tested 35 loci ( P < 1 × 10 −6 ) in a replication cohort of 5,851 cases and 5,866 controls. We identified 17 novel risk loci ( P < 5 × 10 −8 ) in a joint analysis of 26,035 cases and 403,190 controls. We used a neurocentric strategy to assign candidate risk genes to the loci. We identified protein-altering or cis –expression quantitative trait locus ( cis -eQTL) variants in linkage disequilibrium with the index variant in 29 of the 41 PD loci. These results indicate a key role for autophagy and lysosomal biology in PD risk, and suggest potential new drug targets for PD.

Although epigenetic processes have been linked to aging and disease in other systems, it is not yet known whether they relate to reproductive aging. Recently, we developed a highly accurate epigenetic biomarker of age (known as the “epigenetic clock”), which is based on DNA methylation levels. Here we carry out an epigenetic clock analysis of blood, saliva, and buccal epithelium using data from four large studies: the Women’s Health Initiative (n = 1,864); Invecchiare nel Chianti (n = 200); Parkinson’s disease, Environment, and Genes (n = 256); and the United Kingdom Medical Research Council National Survey of Health and Development (n = 790). We find that increased epigenetic age acceleration in blood is significantly associated with earlier menopause (P = 0.00091), bilateral oophorectomy (P = 0.0018), and a longer time since menopause (P = 0.017). Conversely, epigenetic age acceleration in buccal epithelium and saliva do not relate to age at menopause; however, a higher epigenetic age in saliva is exhibited in women who undergo bilateral oophorectomy (P = 0.0079), while a lower epigenetic age in buccal epithelium was found for women who underwent menopausal hormone therapy (P = 0.00078). Using genetic data, we find evidence of coheritability between age at menopause and epigenetic age acceleration in blood. Using Mendelian randomization analysis, we find that two SNPs that are highly associated with age at menopause exhibit a significant association with epigenetic age acceleration. Overall, our Mendelian randomization approach and other lines of evidence suggest that menopause accelerates epigenetic aging of blood, but mechanistic studies will be needed to dissect cause-and-effect relationships further.

A fundamental challenge in the post-genome era is to understand and annotate the consequences of genetic variation, particularly within the context of human tissues. We present a set of integrated experiments that investigate the effects of common genetic variability on DNA methylation and mRNA expression in four human brain regions each from 150 individuals (600 samples total). We find an abundance of genetic cis regulation of mRNA expression and show for the first time abundant quantitative trait loci for DNA CpG methylation across the genome. We show peak enrichment for cis expression QTLs to be approximately 68,000 bp away from individual transcription start sites; however, the peak enrichment for cis CpG methylation QTLs is located much closer, only 45 bp from the CpG site in question. We observe that the largest magnitude quantitative trait loci occur across distinct brain tissues. Our analyses reveal that CpG methylation quantitative trait loci are more likely to occur for CpG sites outside of islands. Lastly, we show that while we can observe individual QTLs that appear to affect both the level of a transcript and a physically close CpG methylation site, these are quite rare. We believe these data, which we have made publicly available, will provide a critical step toward understanding the biological effects of genetic variation.

Expression quantitative trait loci (eQTLs) are genomic regions that regulate gene expression. Here the authors provide a publicly available data set of exon-level eQTLs across the human brain. This includes many genome-wide association study (GWAS) hits for neurological and psychiatric disorders. Germ-line genetic control of gene expression occurs via expression quantitative trait loci (eQTLs). We present a large, exon-specific eQTL data set covering ten human brain regions. We found that cis -eQTL signals (within 1 Mb of their target gene) were numerous, and many acted heterogeneously among regions and exons. Co-regulation analysis of shared eQTL signals produced well-defined modules of region-specific co-regulated genes, in contrast to standard coexpression analysis of the same samples. We report cis -eQTL signals for 23.1% of catalogued genome-wide association study hits for adult-onset neurological disorders. The data set is publicly available via public data repositories and via http://www.braineac.org/ . Our study increases our understanding of the regulation of gene expression in the human brain and will be of value to others pursuing functional follow-up of disease-associated variants.

Microglia are emerging as key drivers of neurological diseases. However, we lack a systematic understanding of the underlying mechanisms. Here, we present a screening platform to systematically elucidate functional consequences of genetic perturbations in human induced pluripotent stem cell-derived microglia. We developed an efficient 8-day protocol for the generation of microglia-like cells based on the inducible expression of six transcription factors. We established inducible CRISPR interference and activation in this system and conducted three screens targeting the ‘druggable genome’. These screens uncovered genes controlling microglia survival, activation and phagocytosis, including neurodegeneration-associated genes. A screen with single-cell RNA sequencing as the readout revealed that these microglia adopt a spectrum of states mirroring those observed in human brains and identified regulators of these states. A disease-associated state characterized by osteopontin (SPP1) expression was selectively depleted by colony-stimulating factor-1 (CSF1R) inhibition. Thus, our platform can systematically uncover regulators of microglial states, enabling their functional characterization and therapeutic targeting.Dräger et al. establish a rapid, scalable platform for iPSC-derived microglia. CRISPRi/a screens uncover roles of disease-associated genes in phagocytosis, and regulators of disease-relevant microglial states that can be targeted pharmacologically.

Single-cell transcriptomics provide a systematic map of gene expression in different human cell types. The next challenge is to systematically understand cell-type-specific gene function. The integration of CRISPR-based functional genomics and stem cell technology enables the scalable interrogation of gene function in differentiated human cells. Here we present the first genome-wide CRISPR interference and CRISPR activation screens in human neurons. We uncover pathways controlling neuronal response to chronic oxidative stress, which is implicated in neurodegenerative diseases. Unexpectedly, knockdown of the lysosomal protein prosaposin strongly sensitizes neurons, but not other cell types, to oxidative stress by triggering the formation of lipofuscin, a hallmark of aging, which traps iron, generating reactive oxygen species and triggering ferroptosis. We also determine transcriptomic changes in neurons after perturbation of genes linked to neurodegenerative diseases. To enable the systematic comparison of gene function across different human cell types, we establish a data commons named CRISPRbrain. Tian et al. conducted a genome-wide CRISPRi/CRISPRa screen in human neurons and uncovered a neuron-specific link among prosaposin, lipofuscin and ferroptosis. The CRISPRbrain data commons enables comparison of gene function across human cell types.

Genetics research in Parkinson's disease has identified over 100 risk loci, yet translating these findings into understanding of disease mechanisms, clinical and pathological heterogeneity, and disease progression remains a challenge. This task requires exploring how genetic risk factors operate over time, interact with environmental factors, and contribute to the diverse ways in which disease manifests. The development of α-synuclein seeding amplification assays (SAAs) offers the opportunity to understand Parkinson's disease pathogenesis and heterogeneity, and drive the development of new disease-modifying and prevention interventions. Emerging biomarker tools, such as α-synuclein SAAs, hold great promise in uncovering the pathological underpinnings of Parkinson's disease and related disorders. Integrating α-synuclein SAAs with genetic data will redefine Parkinson's disease biology and, importantly, identify the temporal sequence of genetic risk, whether that be as a driver of an initiating pathological event or as a response to an initiating stochastic, environmental, or other genetic event. Furthermore, studying genetic and environmental influences in individuals who are asymptomatic but have detectable α-synuclein pathology will provide actionable insights for disease prevention and therapeutic interventions.