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In this review, the authors examine how the identification and analysis of genes associated with ALS have begun to provide insight into the onset and pathology of this motor disease. In addition, they discuss some emerging themes that are poised to inform future efforts to identify further gene targets. Considerable progress has been made in unraveling the genetic etiology of amyotrophic lateral sclerosis (ALS), the most common form of adult-onset motor neuron disease and the third most common neurodegenerative disease overall. Here we review genes implicated in the pathogenesis of motor neuron degeneration and how this new information is changing the way we think about this fatal disorder. Specifically, we summarize current literature of the major genes underlying ALS, SOD1 , TARDBP , FUS , OPTN , VCP , UBQLN2 , C9ORF72 and PFN1 , and evaluate the information being gleaned from genome-wide association studies. We also outline emerging themes in ALS research, such as next-generation sequencing approaches to identify de novo mutations, the genetic convergence of familial and sporadic ALS, the proposed oligogenic basis for the disease, and how each new genetic discovery is broadening the phenotype associated with the clinical entity we know as ALS.

A ~ 1 Mb inversion polymorphism exists within the 17q21.31 locus of the human genome as direct (H1) and inverted (H2) haplotype clades. This inversion region demonstrates high linkage disequilibrium, but the frequency of each haplotype differs across ancestries. While the H1 haplotype exists in all populations and shows a normal pattern of genetic variability and recombination, the H2 haplotype is enriched in European ancestry populations, is less frequent in African ancestry populations, and nearly absent in East Asian ancestry populations. H1 is a known risk factor for several neurodegenerative diseases, and has been associated with many other traits, suggesting its importance in cellular phenotypes of the brain and entire body. Conversely, H2 is protective for these diseases, but is associated with predisposition to recurrent microdeletion syndromes and neurodevelopmental disorders such as autism. Many single nucleotide variants and copy number variants define H1/H2 haplotypes and sub-haplotypes, but identifying the causal variant(s) for specific diseases and phenotypes is complex due to the extended linkage equilibrium. In this review, we assess the current knowledge of this inversion region regarding genomic structure, gene expression, cellular phenotypes, and disease association. We discuss recent discoveries and challenges, evaluate gaps in knowledge, and highlight the importance of understanding the effect of the 17q21.31 haplotypes to promote advances in precision medicine and drug discovery for several diseases. Graphical Abstract

Alzheimer’s disease (AD) is the most common type of dementia, affecting millions of people worldwide; however, no disease-modifying treatments are currently available. Genome-wide association studies (GWASs) have identified more than 40 loci associated with AD risk. However, most of the disease-associated variants reside in non-coding regions of the genome, making it difficult to elucidate how they affect disease susceptibility. Nonetheless, identification of the regulatory elements, genes, pathways and cell type/tissue(s) impacted by these variants to modulate AD risk is critical to our understanding of disease pathogenesis and ability to develop effective therapeutics. In this review, we provide an overview of the methods and approaches used in the field to identify the functional effects of AD risk variants in the causal path to disease risk modification as well as describe the most recent findings. We first discuss efforts in cell type/tissue prioritization followed by recent progress in candidate causal variant and gene nomination. We discuss statistical methods for fine-mapping as well as approaches that integrate multiple levels of evidence, such as epigenomic and transcriptomic data, to identify causal variants and risk mechanisms of AD-associated loci. Additionally, we discuss experimental approaches and data resources that will be needed to validate and further elucidate the effects of these variants and genes on biological pathways, cellular phenotypes and disease risk. Finally, we discuss future steps that need to be taken to ensure that AD GWAS functional mapping efforts lead to novel findings and bring us closer to finding effective treatments for this devastating disease.

Background Parkinson’s disease (PD) is genetically associated with the H1 haplotype of the MAPT 17q.21.31 locus, although the causal gene and variants underlying this association have not been identified. Methods To better understand the genetic contribution of this region to PD and to identify novel mechanisms conferring risk for the disease, we fine-mapped the 17q21.31 locus by constructing discrete haplotype blocks from genetic data. We used digital PCR to assess copy number variation associated with PD-associated blocks, and used human brain postmortem RNA-seq data to identify candidate genes that were then further investigated using in vitro models and human brain tissue. Results We identified three novel H1 sub-haplotype blocks across the 17q21.31 locus associated with PD risk. Protective sub-haplotypes were associated with increased LRRC37A/2 copy number and expression in human brain tissue. We found that LRRC37A/2 is a membrane-associated protein that plays a role in cellular migration, chemotaxis and astroglial inflammation. In human substantia nigra, LRRC37A/2 was primarily expressed in astrocytes, interacted directly with soluble α-synuclein, and co-localized with Lewy bodies in PD brain tissue. Conclusion These data indicate that a novel candidate gene, LRRC37A/2 , contributes to the association between the 17q21.31 locus and PD via its interaction with α-synuclein and its effects on astrocytic function and inflammatory response . These data are the first to associate the genetic association at the 17q21.31 locus with PD pathology, and highlight the importance of variation at the 17q21.31 locus in the regulation of multiple genes other than MAPT and KANSL1 , as well as its relevance to non-neuronal cell types.

Innate immunity is associated with Alzheimer’s disease 1 , but the influence of immune activation on the production of amyloid-β is unknown 2 , 3 . Here we identify interferon-induced transmembrane protein 3 (IFITM3) as a γ-secretase modulatory protein, and establish a mechanism by which inflammation affects the generation of amyloid-β. Inflammatory cytokines induce the expression of IFITM3 in neurons and astrocytes, which binds to γ-secretase and upregulates its activity, thereby increasing the production of amyloid-β. The expression of IFITM3 is increased with ageing and in mouse models that express familial Alzheimer’s disease genes. Furthermore, knockout of IFITM3 reduces γ-secretase activity and the formation of amyloid plaques in a transgenic mouse model (5xFAD) of early amyloid deposition. IFITM3 protein is upregulated in tissue samples from a subset of patients with late-onset Alzheimer’s disease that exhibit higher γ-secretase activity. The amount of IFITM3 in the γ-secretase complex has a strong and positive correlation with γ-secretase activity in samples from patients with late-onset Alzheimer’s disease. These findings reveal a mechanism in which γ-secretase is modulated by neuroinflammation via IFITM3 and the risk of Alzheimer’s disease is thereby increased. The IFITM3 innate immunity protein directly binds presenilin near the active site and upregulates γ-secretase activity and the production of amyloid-β, and IFITM3 is upregulated in patients with late-onset Alzheimer’s disease.

Introduction Diversity in cognition among apolipoprotein E (APOE) ε4 homozygotes can range from early‐onset Alzheimer's disease (AD) to a lifetime with no symptoms. Methods We evaluated a phenotypic extreme polygenic risk score (PRS) for AD between cognitively healthy APOE ε4 homozygotes aged ≥75 years (n = 213) and early‐onset APOE ε4 homozygote AD cases aged ≤65 years (n = 223) as an explanation for this diversity. Results The PRS for AD was significantly higher in APOE ε4 homozygote AD cases compared to older cognitively healthy APOE ε4/ε4 controls (odds ratio [OR] 8.39; confidence interval [CI] 2.0–35.2; P = .003). The difference in the same PRS between APOE ε3/ε3 extremes was not as significant (OR 3.13; CI 0.98–9.92; P = .053) despite similar numbers and power. There was no statistical difference in an educational attainment PRS between these age extreme case‐controls. Discussion A PRS for AD contributes to modified cognitive expression of the APOE ε4/ε4 genotype at phenotypic extremes of risk.

The authors identify mutations in the MATR3 gene as a cause of ALS and dementia in several families. MATR3 is known to bind the ALS-associated protein TDP-43, and at least one of these mutations alters the efficiency of this binding. MATR3 is an RNA- and DNA-binding protein that interacts with TDP-43, a disease protein linked to amyotrophic lateral sclerosis (ALS) and frontotemporal dementia. Using exome sequencing, we identified mutations in MATR3 in ALS kindreds. We also observed MATR3 pathology in ALS-affected spinal cords with and without MATR3 mutations. Our data provide more evidence supporting the role of aberrant RNA processing in motor neuron degeneration.

The authors identified a protective genetic allele associated with lower PU.1 ( SPI1 ) expression in myeloid cells by conducting a genome-wide scan of Alzheimer's disease (AD). PU.1 binds the promoters of AD-associated genes (e.g., CD33 , MS4A4A & MS4A6A , TYROBP ) and modulates their expression, suggesting it may reduce AD risk by regulating myeloid cell gene expression. A genome-wide survival analysis of 14,406 Alzheimer's disease (AD) cases and 25,849 controls identified eight previously reported AD risk loci and 14 novel loci associated with age at onset. Linkage disequilibrium score regression of 220 cell types implicated the regulation of myeloid gene expression in AD risk. The minor allele of rs1057233 (G), within the previously reported CELF1 AD risk locus, showed association with delayed AD onset and lower expression of SPI1 in monocytes and macrophages. SPI1 encodes PU.1, a transcription factor critical for myeloid cell development and function. AD heritability was enriched within the PU.1 cistrome, implicating a myeloid PU.1 target gene network in AD. Finally, experimentally altered PU.1 levels affected the expression of mouse orthologs of many AD risk genes and the phagocytic activity of mouse microglial cells. Our results suggest that lower SPI1 expression reduces AD risk by regulating myeloid gene expression and cell function.

Background Genomic‐informed dementia risk reports (GIDRR) that assess genetic and environmental factors can enhance Alzheimer's disease (AD) risk prediction and prevention. However, most risk models are derived from non‐Latinx White (NLW) populations and lack validation in diverse populations. Here, we evaluate the predictive accuracy of AD clinical and polygenic risk scores (CRS & PRS) in diverse populations and examine their combined effect with family history (FHx) and APOE on incident dementia. Methods In ADSP (N = 18,623; 42% 1KG‐EUR‐like, 25% 1KG‐AMR‐like, 21% 1KG‐AFR‐like, 8.6% 1KG‐SAS‐like, and 0.2% 1KG‐EAS‐like genetic ancestry groups) we constructed three AD‐PRS (excluding APOE): 1KG‐EUR‐like single‐ancestry using clumping and thresholding (CT); multi‐ancestry using CT; and cross‐ancestry using PRS‐CSx‐auto. Logistic regression assessed AD‐PRS associations with AD, adjusting for age, sex, APOE, and PCs. In NACC & ADNI (N = 20,755; 82% NLW, 11% Black, 4.6% Latinx, and 2.8% Asian reported populations), we constructed two CRS—the CAIDE score and its modified version (mCAIDE)—comprising age, gender, education, hypertension, obesity, and dyslipidemia. Logistic regression assessed CRS associations with MCI/AD. Finally, we constructed a GIDRR composed of mCAIDE, FHx, APOE*ε4, and high AD‐PRS‐CSx. Cox‐proportional hazard models estimated risk of dementia progression due to increasing risk burden, adjusting for cohort, race/ethnicity, and CDR. Results In 1KG‐EUR‐like participants, all PRS models predicted higher AD risk, whereas PRS were not predictive in 1KG‐SAS‐like participants (Figure 1). In 1KG‐AFR‐like and 1KG‐AMR‐like participants the 1KG‐EUR‐like AD‐PRS was not associated with AD; however, multi‐ancestry AD‐PRS and PRS‐CSx were predictive of AD risk. Higher CAIDE scores were associated with increased odds of MCI/AD in Asian, Latinx, and NLW participants, but not in Black participants (Figure 2). mCAIDE scores were significantly associated with increased MCI/AD risk in all groups, with the strongest associations in Asian participants and decreasing magnitude through Latinx, NLW, and Black participants. GIDRR analysis found having one high‐risk indicator increased AD risk by 27%, two indicators by 83%, three indicators doubled the risk, and four indicators led to a fivefold increase (Figure 3). Conclusion AD PRS and CRS derived using models with consideration of genetic ancestry and race/ethnicity improve transportability and predictive accuracy. Genomic‐informed risk reports can support equitable, personalized dementia prevention strategies.

Background Biological age, reflecting the cumulative molecular and cellular damage such as telomere attrition, epigenetic alterations and mitochondrial dysfunction, may better capture age‐related decline and Alzheimer’s disease (AD) risk than chronological age. Yet, the independent and interactive contributions of biological age markers for telomere length (TL), epigenetic DNA methylation age (DNAm age), and mitochondrial DNA copy number (mtDNAcn) to AD pathogenesis remain unclear. Methods We estimated blood‐derived TL via qPCR, DNAm age using the CausAge clock from DNAm array, and mtDNAcn from whole genome sequencing in 640 participants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI; Age: 74.95±7.62, Female: 44.2%, cognitively unimpaired: 33.8%, mild cognitive impairment: 51.6%, AD: 14.7%). Linear mixed‐effects models examined the associations and interactions of these markers with a global cognitive composite score, while linear regression tested associations with baseline cerebrospinal fluid (CSF) Aβ42, total‐tau, and phosphorylated tau as well as with cortical thickness and gray matter volume at last visit. Models adjusted for baseline age, sex, clinical dementia rating scale, APOE, blood cell composition, and outcome‐specific covariates (education, scanner, and intracranial volume). Results Individually, TL, DNAm age, and mtDNAcn were not associated with cognition, CSF biomarkers, or neuroimaging outcomes. However, mtDNAcn moderated the association of both TL and DNAm age with baseline cognitive performance such that among individuals with shorter telomeres (β [SE] = 0.033 [0.014], p =0.02) or elevated DNAm age (‐0.049 [0.026], p =0.065), higher mtDNAcn was associated with poorer cognition. Additionally, there was a synergistic interaction between CausAge and TL on CSF Aβ42 (‐4.9e‐05 [1.6e‐05], p =0.002), Aβ42 levels were lower in individuals with higher CausAge and shorter telomeres. Conclusion These findings suggest that increased mtDNAcn may act as a compensatory response to accelerated epigenetic aging and telomere attrition; and that epigenetic age and telomere attrition are associated with greater Ab deposition. Our results underscore the importance of evaluating the interplay among multiple biological aging markers when investigating AD pathogenesis.