Citations

Across multiancestry groups, we analyzed Human Leukocyte Antigen (HLA) associations in over 176,000 individuals with Parkinson’s disease (PD) and Alzheimer’s disease (AD) versus controls. We demonstrate that the two diseases share the same protective association at the HLA locus. HLA-specific fine-mapping showed that hierarchical protective effects of HLA-DRB1 *04 subtypes best accounted for the association, strongest with HLA-DRB1 *04:04 and HLA-DRB1 *04:07, and intermediary with HLA-DRB1 *04:01 and HLA-DRB1 *04:03. The same signal was associated with decreased neurofibrillary tangles in postmortem brains and was associated with reduced tau levels in cerebrospinal fluid and to a lower extent with increased Aβ42. Protective HLA-DRB1 *04 subtypes strongly bound the aggregation-prone tau PHF6 sequence, however only when acetylated at a lysine (K311), a common posttranslational modification central to tau aggregation. An HLA-DRB1 *04-mediated adaptive immune response decreases PD and AD risks, potentially by acting against tau, offering the possibility of therapeutic avenues.

ABSTRACT/SUMMARY Purpose Common LOXL1 protein-altering variants are significant genetic risk factors for exfoliation syndrome (XFS) and the related secondary glaucoma (XFG). A rare LOXL1 missense allele was associated with protective effects in a Japanese cohort, suggesting that other rare alleles may also exhibit protective effects. The goal of this study is to assess the contributions of rare LOXL1 variants to XFS/XFG risk in cases and controls from the United States (US). Methods LOXL1 rare variants (minor allele frequency (MAF) < 1%) were identified from Human exome BeadArray (Illumina) data for 1118 XFS/XFG cases and 3661 controls (Mass Eye and Ear (MEE) cohort) and from exome sequence data for 284 cases and 37,499 controls in All of Us (AoU) The distribution of rare variants, haplotypes, and diplotypes was examined using Fisher exact test. Results Four rare LOXL1 missense alleles, more common in controls, were identified in MEE, P= 7.6E-4), and 456 variants identified in AoU were found only in controls (P=0.045). The rare protective alleles were preferentially located (P= 5.8E-45) in a LOXL1 intrinsic disordered region (IDR) potentially involved in LOXL1 aggregation. Haplotypes that included the rare or minor variants were more common in controls compared to cases in both MEE (Odds Ratio (OR)= 0.21 (95% Confidence interval (CI): 0.19-0.24), P=1.7E-173) and AoU (OR=0.28 (95% CI: 0.23-0.34), P=4.4E-41), and heterozygous diplotypes were also significantly associated with reduced risk overall in both MEE (OR= 0.45 (95% CI: 0.52-0.39), P= 1.7E-89) and AoU (OR=0.26 (95% CI: 0.18-0.33, P=7.6E-28). Diplotypes comprised of only homozygous genotypes were associated with increased disease risk in both MEE and AoU (OR= 4.16 (95% CI: 3.60-4.76), P= 4.2E-89 and 5.26 (95% CI: 4.12-6.73), P=1.87E-42, respectively) and excess homozygosity and decreased heterozygosity was correlated with disease risk for common LOXL1 variants across multi-ethnic populations (P=1.0E-6). Conclusions Using exome array and exome sequence data from XFS/XFG cases and controls from the United States, we identified rare protective LOXL1 missense variants and show that the distribution of the corresponding haplotypes and diplotypes was associated with lower risk of XFS/XFG. Diplotype results also demonstrated that LOXL1 allelic heterozygosity was inversely associated, while homozygosity was associated with increased disease risk. These results suggest that LOXL1 MAF variation among populations, with corresponding variation in genotype heterozygosity and homozygosity, determines the XFS/XFG association.

AbstractBackgroundDigital pathology and machine learning (ML) workflows have paradigm shifting potential especially in the field of Alzheimer’s disease and related disorders. However, many institutions/centers may not have access to these technologies. To provide benchmark data, a survey was developed and distributed to National Institutes of Health’s Alzheimer’s Disease Centers (ADCs) in the United States.MethodSurvey questions covered topics such as: infrastructure (i.e. type of digital slide scanners used), funding sources (i.e. how the scanner was funded), and data management/storage (i.e. size of digital files). After development, review, and approval by the ADC digital pathology working group, the survey was distributed via email to 35 past and current ADC directors and/or ADC neuropathology core leaders. Participation in the survey was completely voluntary and answers did not contain any personal data.ResultThe survey generated over a 90% response rate, and the majority of those who completed the survey were neuropathology core leaders; 81% stated their ADC had access to a digital slide scanner, most common brand being Aperio/Leica. One third of respondents stated there was a fee for service to utilize the scanner. For digital pathology and/or ML resources, 40% of respondents stated none are supported in any way by their ADC. To cover the purchase and operation of the scanner, 50% stated they had institutional support. Many were unsure of the approximate average scanned file size of digital images (37%) and total amount of storage space that files occupied (50%). Many (75%) were aware of other departments at their institution working with digital pathology and/or ML, but a similar percentage was unaware of multi‐university or industry partnerships.ConclusionThese results demonstrate many ADCs have access to a digital slide scanner and had institutional support to cover the purchase. However, further investigation is needed to understand hurdles and barriers for implementing both digital pathology and ML workflows aiding in standardized methods across ADCs.

Background: Long QT syndrome (LQTS) is a rare genetic disorder and a major preventable cause of sudden cardiac death in the young. A causal rare genetic variant with large effect size is identified in up to 80% of probands (genotype positive) and cascade family screening shows incomplete penetrance of genetic variants. Furthermore, a proportion of cases meeting diagnostic criteria for LQTS remain genetically elusive despite genetic testing of established genes (genotype negative). These observations raise the possibility that common genetic variants with small effect size contribute to the clinical picture of LQTS. This study aimed to characterize and quantify the contribution of common genetic variation to LQTS disease susceptibility. Methods: We conducted genome-wide association studies followed by transethnic meta-analysis in 1656 unrelated patients with LQTS of European or Japanese ancestry and 9890 controls to identify susceptibility single nucleotide polymorphisms. We estimated the common variant heritability of LQTS and tested the genetic correlation between LQTS susceptibility and other cardiac traits. Furthermore, we tested the aggregate effect of the 68 single nucleotide polymorphisms previously associated with the QT-interval in the general population using a polygenic risk score. Results: Genome-wide association analysis identified 3 loci associated with LQTS at genome-wide statistical significance ( P <5×10 −8 ) near NOS1AP , KCNQ1 , and KLF12 , and 1 missense variant in KCNE1 (p.Asp85Asn) at the suggestive threshold ( P <10 −6 ). Heritability analyses showed that ≈15% of variance in overall LQTS susceptibility was attributable to common genetic variation ( h2SNP 0.148; standard error 0.019). LQTS susceptibility showed a strong genome-wide genetic correlation with the QT-interval in the general population (r g =0.40; P =3.2×10 −3 ). The polygenic risk score comprising common variants previously associated with the QT-interval in the general population was greater in LQTS cases compared with controls ( P <10−13), and it is notable that, among patients with LQTS, this polygenic risk score was greater in patients who were genotype negative compared with those who were genotype positive ( P <0.005). Conclusions: This work establishes an important role for common genetic variation in susceptibility to LQTS. We demonstrate overlap between genetic control of the QT-interval in the general population and genetic factors contributing to LQTS susceptibility. Using polygenic risk score analyses aggregating common genetic variants that modulate the QT-interval in the general population, we provide evidence for a polygenic architecture in genotype negative LQTS.

Adenosine monophosphate–activated protein kinase (AMPK) is a major energy sensor that maintains cellular energy homeostasis. Huntington’s disease (HD) is a neurodegenerative disorder caused by the expansion of CAG repeats in the huntingtin (Htt) gene. In this paper, we report that activation of the α1 isoform of AMPK (AMPK-α1) occurred in striatal neurons of humans and mice with HD. Overactivation of AMPK in the striatum caused brain atrophy, facilitated neuronal loss, and increased formation of Htt aggregates in a transgenic mouse model (R6/2) of HD. Such nuclear accumulation of AMPK-α1 was activity dependent. Prevention of nuclear translocation or inactivation of AMPK-α1 ameliorated cell death and down-regulation of Bcl2 caused by mutant Htt (mHtt). Conversely, enhanced expression of Bcl2 protected striatal cells from the toxicity evoked by mHtt and AMPK overactivation. These data demonstrate that aberrant activation of AMPK-α1 in the nuclei of striatal cells represents a new toxic pathway induced by mHtt.