Reference Panel Research Articles

Genome‐wide identification of modifiers of age‐at‐onset for Alzheimer’s disease in African American populations

AbstractBackgroundSeveral studies have attempted to identify genes for age‐at‐onset (AAO) of Alzheimer’s disease (AD) through genome‐wide linkage and genome‐wide association studies (GWAS). While these efforts have thus far focused predominantly on non‐Hispanic white (NHW) populations, we present here the first GWAS to identify genetic contributors to AAO in African Americans (AA) using AA genotype and phenotype data from the Alzheimer’s Disease Genetics Consortium (ADGC).MethodWe combined data from 13 AA prospective and case‐control ADGC datasets, excluding family‐based datasets. Genotype data underwent standard quality control and were imputed to the TOPMed R5 reference panel using the Michigan Imputation Server. Data were merged across cohorts using QCTOOL and GTOOL, filtering out variants with MAF≤0.005). We performed two analyses: case‐only linear mixed‐model regression with AAO as outcome (LMM); and survival analysis using Cox proportional‐hazards frailty modeling (COXPHF) with time‐to‐AD‐onset (AAO in cases and censoring of controls at age‐at‐last‐exam). Both models were adjusted for sex, principal components capturing population substructure, and APOE‐ε4 dosage with a random cohort effect.ResultWe examined 2,262 AA AD cases, including 1,561 females (69%) with mean (SD) AAO of 77.7 (8.1) years. The APOE‐adjusted COXPHF analyses identified twelve genome‐wide significant regions (P<5×10−8), the most significant in ABCA7 (P = 3.57×10−10), known to be associated with AD risk in AAs. In the LMM analysis, we observed strong novel associations with variants in CCDC141 on chr2q31.2 (Pmin = 2.93×10−9). In silico analyses of LD structure and functional potential suggest SESTD1, a gene involved in synaptic regulation, as driving the CCDC141 locus signal. Nine of 12 COXPHF loci were driven by African‐specific variants (MAF<0.0002 in gnomAD Non‐Finish Europeans). These significant loci identified in the AA COXPHF or LMM analyses were not significant (P>0.05) in equivalent analyses in NHW ADGC cohorts (9,220 AD cases/10,350 controls; Li et al. Alz Dement 2023), except for the ABCA7 locus (NHW P<0.0002).ConclusionIn a large ADGC African American dataset, we confirmed AAO associations in the APOE region and ABCA7 and observed evidence for potential novel AD AAO loci including SESTD1; many of which might be African‐ancestry specific.

Identification of rare coding variants associated with Alzheimer’s disease.

AbstractBackgroundPrevious whole exome sequencing (WES) studies of Alzheimer’s disease (AD) have identified genome‐wide significant associations with rare variants in several novel genes and highlighted the need for investigations in larger samples. We combined WES and whole genome sequencing (WGS) data assembled by the Alzheimer Disease Sequencing Project (ADSP) to increase the power for detecting associations of AD with rare variants in gene coding regions.MethodWe developed an efficient computational pipeline to perform both pre‐merging and post‐merging genotype, variant and sample‐level quality control (QC) on WGS data containing 16,905 individuals and WES data for 20,504 individuals. The resultant sample included participants from European (EA, 11,279 AD cases, 8,924 controls), African American (AA, 2,757 AD cases, 4,336 controls), and Caribbean Hispanic (CH 1,438 AD cases, 3,256 controls) ancestries. We employed GENESIS to test association of AD with 250,465 bi‐allelic QC’d variants using a logistic model including covariates for age, sex, exome capture kit, read length, and ancestry principal components (PCs).ResultIn the total sample, variants from APOE and other known AD genes including SORL1 (P = 5.30×10‐7), NECTIN2 (P = 6.94×10‐7), and TREM2 R47H (P = 2.34×10‐13) crossed or neared the study‐wide significance (SWS) threshold of P = 2.00×10‐7 (0.05/250,465). SWS or borderline significant associations were also found with variants in several novel loci including TKTL2 (P = 2.35×10‐8), D2HGDH, (P = 1.09×10‐7), CECR1 (P = 4.02×10‐7), PDHA2 (P = 2.76×10‐7), GOLGA1 (P = 1.72×10‐7), CYLD (P = 1.84×10‐7), and RP11‐243M5.4 (P = 1.37×10‐7). PSEN1 missense mutation G206A (rs63750082) previously associated with early onset AD in the CH group, was significantly associated with late onset AD in the same population (P = 1.58×10‐13). SWS association of AD with APOE was observed in all groups. Significant associations were also observed with variants in SERPINB8 (P = 3.77×10‐9) and FAM171A (P = 7.20×10‐7) in EAs and TLR4 (P = 4.58×10‐7) in CH. Associations with several top‐ranked variants were replicated in the Alzheimer’s Disease Genetics Consortium GWAS dataset that were imputed using the TOPMed reference panel and ADSP 5K WGS dataset.ConclusionWe demonstrated that merging WGS and WES datasets can increase power to detect associations with rare coding variants in genes including ones previously implicated in AD (CYLD and TLR4) and early‐onset stroke (CECR1).

Familial relatedness in genetic frontotemporal dementia cohorts: findings from the international Frontotemporal Dementia Prevention Initiative

AbstractBackgroundGiven the rarity of genetic frontotemporal dementia (FTD), researchers across the world have come together to form the FTD Prevention Initiative (FPI) in an effort to improve prevention trials design. As this initiative begins to bring together large‐scale data from worldwide cohort series, including ALLFTD in North America and GENFI in Europe and Canada, it is critical for FPI to quantify the level of relatedness between all participants. Here we provide the most recent update to these ongoing analyses.MethodsGenome‐wide SNP genotyping data from 1,684 ALLFTD and 568 GENFI participants was used to perform lineage analyses using PLINK. Briefly, QC was performed similarly in all datasets to remove individuals with low call rate and filter autosomal SNPs for missingness, frequency, and deviation from Hardy‐Weinberg equilibrium. Genetic ancestry was inferred by projecting genotyped samples into the principal components of the 1000 Genomes reference panel, using R package bigsnpr. Overlapping ALLFTD and GENFI genotyping data was then used, in a two‐stage approach, to calculate pairwise identity‐by‐descent (IBD) estimates and KING coefficients, followed by family‐network identification and pedigree reconstruction using PRIMUS.ResultsFirst, we calculated IBD estimates among all participants by restricting pairs to those with estimates>0.1875 (up to second‐degree relatives). Overall, we identified a total of 292 second‐degree family networks, including 168 ALLFTD and 120 GENFI families, mostly associated with pathogenic variants in the 3 major FTD‐causing genes. We also identified 4 family networks with participants enrolled in both the ALLFTD and GENFI series, as well as several multi‐site families within the ALLFTD consortium. This first, overall approach allowed us to predict close relationships even between individuals with different ancestral backgrounds, including at least 4 confirmed admixed families. More distant relationships were also detected within ALLFTD and GENFI by performing ancestry‐based analysis among participants with estimated European ancestry, using the KING‐robust algorithm.ConclusionsThese lineage analyses allowed us to identify, otherwise unknown, close (and distant) relatives from different study sites, as well as within the ALLFTD and GENFI series. This dataset will be a crucial resource to increase statistical accuracy and power in upcoming collaborative FPI studies.

Multi‐Ancestry Genome‐wide Association Analysis of Late‐Onset Alzheimer’s Disease (LOAD) in 60,941 Individuals Identifies Multiple Novel Cross‐Ancestry Associations and Implicates Amyloid and Complement Pathways

AbstractBackgroundLack of diversity in expanding genomic studies has limited the identification of LOAD risk variants that may be more prevalent in non‐European ancestry groups with more modest power requirements for detection. To help reverse this trend, we constructed and analyzed a multi‐ancestry collection of GWAS datasets in the Alzheimer’s Disease Genetics Consortium (ADGC) to identify novel shared and ancestry‐unique LOAD susceptibility loci and related biological pathways.MethodThe multi‐ancestry data collection of the ADGC includes GWAS genotype and phenotype data on 38,774 non‐Hispanic White (NHW), 7,454 African American (AA), 11,436 Hispanic (HI), and 3,277 East Asian (EAS) subjects imputed to the NHLBI TOPMed v5 reference panel. We performed a two‐stage analysis: (1) single‐variant association using score‐based logistic regression for population‐based datasets and generalized linear mix‐models for family studies with covariate adjustment for onset/exam age, sex, principal components for population substructure, and APOE ε2/ε3/ε4 genotype, followed by within‐ancestry fixed‐effects meta‐analysis using METAL; and (2) cross‐ancestry meta‐analysis of within‐ancestry associations using random‐effects modeling (RE2) in METASOFT. Secondary analyses include pathway analysis using EnrichR and gene‐based association testing using SKAT‐O (on‐going).ResultIn addition to APOE region associations, we identified 13 loci with genome‐wide significant (GWS; P≤5×10−8) cross‐ancestry associations including chromosomes 1q32.2 (CR1), 2q14 (BIN1), 6p21.1 (TREM2), 6p12.3 (CD2AP), 8p21.2 (PTK2B), 8p21.1 (CLU), 8q24.3 (SHARPIN), 11q12 (MS4A6A), 11q14 (PICALM), 19p13.3 (ABCA7), and novel loci at 11p2 (LRRC4C) and 12q24.13 (LHX5‐AS1). An additional 13 loci reached suggestive significance (P<10−5), including loci with ancestry‐specific associations attaining GWS such as PALM2AKAP2 (P = 2.5×10−8 in EAS), GRB14 (P = 1.7×10−8 in HI), and KIAA0825 (P = 2.9×10−8 in NHW). Follow‐up pathway analysis implicated multiple amyloid regulation pathways (strongest: negative regulation of APP catabolism, adjusted P = 1.6×10−4) and the classical complement pathway (adjusted P = 1.3×10−3). Follow‐up analyses including fine‐mapping and gene‐based analyses are on‐going.ConclusionCross‐ancestry GWAS meta‐analyses identified novel LOAD susceptibility loci in/near LRRC4C and LHX5‐AS1, both with known roles in neuronal development, as well as several novel ancestry‐unique loci, showing their tremendous value for gene discovery with smaller sample sizes than current European ancestry LOAD GWAS. Even larger multi‐ancestry studies will provide even more power for further elucidating the genomics of LOAD.

Aberrant landscapes of maternal meiotic crossovers contribute to aneuploidies in human embryos.

Meiotic recombination is crucial for human genetic diversity and chromosome segregation accuracy. Understanding its variation across individuals and the processes by which it goes awry are long-standing goals in human genetics. Current approaches for inferring recombination landscapes rely either on population genetic patterns of linkage disequilibrium (LD)-capturing a time-averaged view-or on direct detection of crossovers in gametes or multigeneration pedigrees, which limits data set scale and availability. Here, we introduce an approach for inferring sex-specific recombination landscapes using data from preimplantation genetic testing for aneuploidy (PGT-A). This method relies on low-coverage (<0.05×) whole-genome sequencing of in vitro fertilized (IVF) embryo biopsies. To overcome the data sparsity, our method exploits its inherent relatedness structure, knowledge of haplotypes from external population reference panels, and the frequent occurrence of monosomies in embryos, whereby the remaining chromosome is phased by default. Extensive simulations show our method's high accuracy, even at coverages as low as 0.02×. Applying this method to PGT-A data from 18,967 embryos, we mapped 70,660 recombination events with ∼150 kbp resolution, replicating established sex-specific recombination patterns. We observed a reduced total length of the female genetic map in trisomies compared with disomies, as well as chromosome-specific alterations in crossover distributions. Based on haplotype configurations in pericentromeric regions, our data indicate chromosome-specific propensities for different mechanisms of meiotic error. Our results provide a comprehensive view of the role of aberrant meiotic recombination in the origins of human aneuploidies and offer a versatile tool for mapping crossovers in low-coverage sequencing data from multiple siblings.

X‐chromosome wide association study for Alzheimer’s disease

AbstractBackgroundAlthough the X‐chromosome represents about 5% of the genome, it has been excluded from the major genome‐wide association studies on Alzheimer’s Disease (AD) due to its genetic specificities. We performed an in‐depth X‐Chromosome‐Wide Association Study (XWAS) to better characterize the genetic landscape of AD.MethodThe XWAS is based on 49,333 clinically diagnosed cases and 68,882 controls (including 31,314 female cases and 39,407 female controls) of European ancestry from 29 studies from the International Genomics of Alzheimer’s Project (IGAP) and the European Alzheimer &amp; Dementia Biobank (EADB) consortia. 45,993 samples were imputed with the 1000G reference panel and 72,220 samples were imputed with the TOPMed panel.We considered three approaches to take into account the different inactivation scenarios on the X‐chromosome: 1) random X‐chromosome inactivation (r‐XCI) in females, equivalent to an additive genetic model with males coded as homozygous females; 2) skewed X‐chromosome inactivation in females, where a dominance effect was added to the r‐XCI model to capture the inactivation skewedness; 3) escape X‐chromosome inactivation in females, equivalent to an additive model with males coded as hemizygous. For each approach, we performed a single variant analysis with a meta‐analysis of the 29 studies, followed by a gene‐based analysis.ResultWe analyzed 404,688 variants, including 225,045 common variants (Minor Allele Frequency [MAF] &gt; 1%). No genome‐wide significant signals were found in either approach, but three suggestive signals (p‐value &lt; 1×10‐5) were identified in the r‐XCI approach. In one of these loci, we detected an X‐chromosome‐wide significant gene with the gene‐based analysis (p‐value = 5.45×10‐5). The top variant of this locus shows a similar effect in males and females (odds ratio [OR] = 0.93, 95% confidence interval [CI] = 0.90–0.96, p‐value = 8.63 × 10−6, and MAF = 32%, with OR[CI] in females = 0.86[0.79‐0.94], and OR[CI] in males = 0.92 [0.87‐0.97]).ConclusionWe identified promising genetic signals for AD on the X‐chromosome. To increase power, we are currently updating the imputation with TOPMed for all the studies and extending the analyses to large European biobanks.

Not all regions are created equal: identifying regions and cell types associated with cognitive resilience in the AD‐BXD model population

AbstractBackgroundThe relationship between regional cell composition, brain pathology, and memory impairment in Alzheimer’s disease (AD) remains incompletely understood. The specific brain regions and tracts (and their interactions) that explain the heterogeneity of cognitive decline with AD are not clear. By integrating brain‐wide immunohistochemistry and cognitive outcomes we can achieve unbiased detection of regions of interest (ROIs) and identify cellular correlates of cognitive resilience for causal testing.MethodImmunohistochemistry(IHC) was completed to evaluate neurodegeneration (NeuN), gliosis (Iba1&amp;GFAP), amyloid beta(Aβ) pathology(AB1‐42), and cell bodies(Thionine) in adult (6 months(m)) and middle‐aged (14m) mice of the AD‐BXD genetic reference panel (n = 227). Using the QUINT workflow, hemibrain slices were systematically segmented and registered to the Allen Brain Atlas to gain a global perspective of percent cell and pathology coverage. IHC traits were correlated with contextual fear conditioning outcomes to identify regions whose stain composition is associated with memory performance.ResultsContrary to our prior work using ELISA‐based Aβ measurement, we find that Aβ quantified via IHC at the presymptomatic time point (6m) is strongly correlated with differences in short‐ and long‐term memory in 14m female 5XFAD carriers. Furthermore, the degree of astrogliosis at 6m in cortical, striatal, and thalamic regions acts as a predictor of cognitive outcomes at 14m. While age‐related decreases in NeuN load were not observed, wide variation in neurodegeneration levels could be attributed to strain differences and 14m NeuN load was positively correlated with 14m long‐term memory among this female 5XFAD population. Highlighting the importance of genetic background on AD progression, we were able to categorize strains as resilient or susceptible to pathological and cognitive decline and evaluate the overlap of these traits. Strains that exhibit the unique identity of being pathologically susceptible but cognitively resilient offer a novel opportunity to investigate the underlying mechanisms of protection from cognitive decline with AD.ConclusionIntegrating brain‐wide IHC and behavioral data, we were able to identify regional and cellular correlates that may predict downstream cognitive outcomes. Detection of these biomarkers may prove a valuable resource to disseminate the insidious prodromal stages of AD in which biochemical changes precede apparent clinical symptoms.

TREM2 Burden associates solely with Alzheimer’s Disease, and decreases the Chance to become a Centenarian

AbstractBackgroundRare TREM2 variants are major risk factors for Alzheimer’s disease (AD), but TREM2 variants may also confer a higher risk for other neurodegenerative diseases and a lower probability for cognitively healthy aging. We studied the TREM2 burden associated with different types of dementia and cognitively healthy centenarians (CHCs).MethodWe included participants of the 100‐Plus Study, Amsterdam Dementia Cohort, Longitudinal Aging Study Amsterdam and various Dutch memory clinics. TREM2 variants (R47H, R62H, Q33X, R62C, T96K) were genotyped with a high density array or imputed using standard methods (TOPMED reference panel). To avoid family bias and ethnic differences, related individuals and those of non‐European ancestry were excluded. Frequencies of individual variants and the burden of TREM2 variants were compared in AD dementia, dementia with Lewy Bodies (DLB), frontotemporal dementia (FTD), cognitively normal controls and CHCs (correcting for 5 principal components).ResultWe identified 242 carriers of TREM2 mutations and 6,683 controls without a TREM2 mutation with a mean age of 69 years (SD ±14 years), 50% female (Table 1). TREM2 variants were significantly associated with AD dementia (OR 1.4, 95%CI 1.1‐1.8, p = 0.01) (Table 2). R47H conferred the highest risk for AD (OR 2.8, 95%CI 1.4‐5.6, p = 0.004), compared to 1.3‐fold increased risk of R62H (95%CI 0.9‐1.7, p = 0.11). The carrier frequency was not increased in DLB (OR 1.4, 95%CI 0.7‐2.6, p = 0.34) and was not increased in FTD compared to controls (OR 0.59, 95%CI 0.3‐1.3, p = 0.18). Of interest, the allele frequency of TREM2 variants in centenarians is half of the expected frequency (OR = 0.46, 95%CI 0.1‐1.1, p = 0.10), and only concerns R62H.ConclusionWe replicate the association of TREM2 with increased risk of AD. In contrast to previous reports no association was observed with DLB or FTD. Cognitively healthy centenarians show a negative trend for TREM2 allele frequency suggesting that carrying a TREM2 variant decreases chances of survival to extreme age.

A new risk locus on chromosome 1 is suggested by genome‐wide association study in Peruvians for Alzheimer disease

AbstractBackgroundIncreasing ethnic/ancestral diversity in genetic studies is critical for defining the genetic architecture of Alzheimer disease (AD). Amerindian (AI) populations are substantially underrepresented in AD genetic studies. The Peruvian (PE) population, with up to ∼80% of AI ancestry, provides a unique opportunity to assess the role of AI ancestry in AD. We performed the first genome‐wide association study (GWAS) in the PE population to identify novel AD susceptibility loci and characterize known AD genetic risk loci.MethodThe PE dataset includes array‐genotype and phenotype data from 542 individuals (189 cases; 353 controls), imputed to the NHLBI TOPMedv5 haplotype reference panel. We used a generalized linear mixed‐model (SAIGE software) for the GWAS analysis. We analyzed two separate models; the first model accounted for sex, age, and population substructure, while the second model also included the dosage of APOEe4. In both models, we included a genetic relationship matrix as a random effect to account for any potential relatedness. To determine if the associations are specific to specific ancestries, we employed ancestry‐aware approaches using the RFMix software.ResultAPOE was significantly associated with AD with an effect size comparable to that found in non‐Hispanic white (NHW) populations (OR = 3.3(2.2‐4.8),pv = 8.0×10−10). Two additional known AD loci, TREML2 (pv = 0.008) and CLU (pv = 0.012), showed nominal significance Variants at three additional loci reached suggestive significance (pv&lt;1×10−6): NFASC (pv = 9.4×10−8;chromosome 1), STK32A (pv = 9.3×10−7; chromosome 5), and LOC100132830 (pv = 6.7×10−7;chromosome 6). The NFASC locus neared genome‐wide significance in the APOE adjusted model (pv = 6.7×10−8). The haplotypes associated with AD at the NFASC locus were found to be of European origin. Additionally, the STK32A locus was found to have a protective effect specifically among individuals of AI background. We did not observe significant heterogeneity of effect at the APOE and LOC100132830 loci across different ancestral backgrounds.ConclusionPE GWAS identified a novel, promising AD susceptibility locus in the NFASC gene of European origin. We also detected a potential protective effect in the STK32A locus on AI background, emphasizing the importance of incorporating ancestry‐aware approaches in gene discovery in admixed populations.

Dementias Platform UK: Bringing genetics into life

AbstractBackgroundDPUK is a data repository bringing together a wide range of population and clinical cohorts from the UK, Europe and South Korea. It enables data discovery, variable selection, and data access for multi‐modal, multi‐cohort analysis in a shared and secure environment. Neurodegenerative dementias are group of diseases with highly heterogeneous pathology and with an overlapping genetic component that is poorly understood. Combing genetic data from different studies is important due to the increase in power this provides, but this presents an additional challenge due to differences in genotyping arrays and lack of overlapping variants.MethodWe have curated and harmonized genome‐wide data from 6 studies (Brains for Dementia Research, EPIC Norfolk, Generation Scotland, Airwave‐chip 1, Airwave‐chip 2, MRC National Survey of Health Development (NSHD)) within the DPUK platform. We created a pipeline that performs rigorous quality‐control (QC) analysis and imputes genetic variance with the 1000 Genome reference panel using the minimac algorithm. Further, standard pruning and thresholding Polygenic Risk Score (PRS) have been generated with 5 summary statistics related to neurodegenerative diseases (clinical AD, clinical/proxy AD, FTD, ALS, PD) for all 6 studies separately and for the combined dataset.ResultResearch‐ready imputed genetic data that have undergone QC and the PRS, based upon the latest neurodegenerative GWAS, are available for the 6 cohorts separately, and for the combined dataset of 60,670 individuals.ConclusionPreparing multiple datasets to a common standard for research‐readiness increases scientific opportunity and allows the wider research community to access and process data at scale and pace.

Isoform-level transcriptome-wide association uncovers genetic risk mechanisms for neuropsychiatric disorders in the human brain

Methods integrating genetics with transcriptomic reference panels prioritize risk genes and mechanisms at only a fraction of trait-associated genetic loci, due in part to an overreliance on total gene expression as a molecular outcome measure. This challenge is particularly relevant for the brain, in which extensive splicing generates multiple distinct transcript-isoforms per gene. Due to complex correlation structures, isoform-level modeling from cis-window variants requires methodological innovation. Here we introduce isoTWAS, a multivariate, stepwise framework integrating genetics, isoform-level expression and phenotypic associations. Compared to gene-level methods, isoTWAS improves both isoform and gene expression prediction, yielding more testable genes, and increased power for discovery of trait associations within genome-wide association study loci across 15 neuropsychiatric traits. We illustrate multiple isoTWAS associations undetectable at the gene-level, prioritizing isoforms of AKT3, CUL3 and HSPD1 in schizophrenia and PCLO with multiple disorders. Results highlight the importance of incorporating isoform-level resolution within integrative approaches to increase discovery of trait associations, especially for brain-relevant traits.

Deliberating with purpose: Deliberative civic engagement for health policy

AbstractThis article seeks to understand why deliberative civic engagement is chosen as a method of engagement by policymakers, using two jurisdictions as exploratory cases: the Nova Scotia Health Authority's Community Conversations about Collaborative Family Practice Teams and Algoma Ontario Health Team's Citizen Reference Panel on Integrated Care. The purpose is to interrogate a presumption that deliberative civic engagement is choice driven by an alignment between the goals of engagement and theories of deliberation. I find that in both instances, policymakers chose deliberative civic engagement largely because of situational factors, rather than through the theoretical claims of different methods of engagement and the goals of the engagement activity. I argue that for practitioners seeking to embed deliberative processes, greater consideration should be given to the contextual factors that enable or inhibit the commissioning of such activities.

Highly Sensitive Chip-Based Digital PCR Platform for Quantitative Detection of BCR::ABL1 Transcripts throughout CML Treatment

Introduction: With various BCR::ABL1 tyrosine kinase inhibitors (TKIs), chronic myeloid leukemia (CML) has become a manageable disease and current therapeutic goal is treatment-free remission (TFR). To achieve a successful TFR in more patients, a precise assessment of minimal residual disease (MRD) is one of the prerequisite requirements. Since undetectable BCR::ABL1 fusion transcripts by conventional Taqman™-based quantitative polymerase chain reaction (qPCR) is not an indicator for complete eradication of the CML clone, it requires the development of more sensitive technologies. Currently, to overcome some limitations of conventional qPCR, such as rigorous standardization process and variations in sensitivity between laboratories, digital quantitative-PCR (dqPCR) methods have been developed for accurate and precise detection and its use in the routine clinical practice is gradually expanding. However, current dqPCR methods require the inclusion of one or more negative partitions to calculate the concentration using Poisson distribution. Consequently, this leads to a more than a 10-fold decrease in the maximum detectable concentration in a single test compared to conventional qPCR. Therefore, we have developed a novel technology, High Dynamic Range Digital Real-time PCR (so called HDR-drPCR) to achieve wider dynamic range, which allows more stable, accurate and sensitive monitoring of BCR::ABL1 in a timely manner. Methods: For linearity assessment, we used BCR::ABL1 positive (e14a2) K562 cell line diluted to 7 points by 10-fold serial dilutions from 25 to 2.5x10 -5 %IS with BCR::ABL1 negative HL60 cells. In HDR-drPCR, the GUSB gene was employed as a control gene to determine %IS values. For this purpose, the 1 st WHO international genetic reference panel was utilized to calculate the correction factor (CF). With the results from cell lines, we also evaluated equivalence between conventional qPCR and HDR-drPCR using 219 clinical specimens. Among them, 100 samples were determined as DMR (&amp;lt;0.01%IS) based on the qPCR test results In detail, conventional qPCR was performed using Transcriptor First Strand cDNA Synthesis Kit (Roche, USA) for cDNA synthesis and Real-Q BCR-ABL Quantification Kit (Biosewoom, South Korea) for qPCR. For HDR-drPCR (1-step reverse transcriptase PCR), 10 6 to 10 7 copies per reaction of GUSB gene were applied to disposable cartridges of Genotizer™ HDR BCR::ABL1 Major IS detection kit (Optolane Technologies, South Korea) with LOAA platform (Optolane Technologies, Korea). Based on the results, correlation analysis between qPCR and HDR-drPCR was performed using correlation graphs and Blend-Altman plots. Results: Linearity was assessed by the dilution of RNA of K562 with RNA of HL60 using 10-fold serial dilution of up to - 7 log. The result showed accurate linearity (R 2 = 0.9972) at the range of BCR::ABL1/GUSB ratio of 10 1 to 10 -5(%). Notably, HDR-drPCR technology allowed to detect the level of BCR::ABL1 transcript of MR 6.34 (0.00005 %IS) (Figure 1A). The correlation analysis for 209 clinical samples showed that measured values from both qPCR and HDR-drPCR were closely correlated with the R 2 of 0.973 1 (Figure 1B) . The Bland-Altman plot showed a mean bias of 0.159, and the limit of agreement at the 95% confidence interval (LOA95) was calculated as -0.387 to 0.705. Furthermore, the concordance rate between the two methods was 96.17%, as measured by the proportion of samples in which the difference between the two methods was within a factor of 5. This indicates a strong concordance between the two methods. HDR-drPCR reliably detected BCR::ABL1 transcripts in all 90 clinical specimens measured below 0.01%IS (DMR) using qPCR. Additionally, HDR-drPCR detected trace amounts of BCR::ABL1 transcripts in 6 out of 10 specimens that were not detected by qPCR, showcasing its improved sensitivity compared to the conventional qPCR method. Conclusion: Taken together, we believe our high dynamic range real-time digital PCR(HDR-drPCR) may minimize false positive results and maximize the analytical sensitivity of detecting BCR::ABL1 fusion transcripts and thus, would be useful for accurately assessing treatment in routine clinical practice and facilitating the application of treatment-free remission (TFR). We will include these results in further intensive studies focusing on DMR clinical specimens Study support: Funded by Korea Research Foundation

Genetic Variants in Canonical Wnt Signaling Pathway Associated with Pediatric ITP

Introduction : Pediatric immune thrombocytopenia (ITP) is thought to develop when a triggering event inappropriately activates an autoimmune anti-platelet response in the context of predisposing genetic factors. Inborn errors of immunity are increasingly being identified in cases of chronic, refractory autoimmune cytopenias. We sought to identify genetic variants associated with predisposition to 1) primary or secondary pediatric ITP of any disease duration versus healthy controls and 2) chronic ITP (cITP) versus disease that spontaneously resolves in &amp;lt; 1 year (sr-ITP). Methods : DNA and clinical data were derived from 8 sites from the Pediatric ITP Consortium of North America's (ICON) biorepository. Samples were genotyped using the Illumina Global Screening Array BeadChip. Genotypes were imputed using the Michigan Imputation Server HRC reference panel. Genetic variants that passed standard quality metrics and had a MAF ≥1% were retained. Control samples (n=8,372) were obtained from the National Longitudinal Study of Adolescent to Adult Health (Add Health) cohort. Logistic regression models were used to estimate adjusted odds ratios (aORs) comparing (1) ITP and control cohorts and (2) cITP and sr-ITP cohorts. Models assumed additive allelic effects and accounted for the top 3 principal components. Genome-wide significance was defined as P &amp;lt;5 × 10 -8 and suggestive of genome-wide significance, P &amp;lt;1 x 10 -5. Results : Six-hundred ten unique patient samples were genotyped. Nineteen (3.1%) did not pass quality control, leaving 591 for analysis. This cohort included 307 (52.0%) cITP patients, 209 (35.4%) sr-ITP patients, and 75 (12.7%) individuals without complete follow-up data to allow for classification of cITP or sr-ITP. The ITP cohort was 50.1% male, 50.1% non-Hispanic (NH) white, 29.4% Hispanic, 6.1% NH Black, 3.1% NH Asian, and 11.3% Other/Unknown. Compared with healthy controls, we identified 6 loci associated with ITP at genome-wide significance (Figure 1). Located within the intronic region of SLC24A4 rs75650997 was associated with an increased risk of ITP compared with controls (aOR: 2.38, P=3.9x10 -8). An intronic variant, rs2165798, in NAV2 was inversely associated with ITP (aOR: 0.52, P=3.2x10 -11). A variant in NKD1 rs4785216, was inversely associated with ITP (aOR: 0.43, P=8.86x10 -15).Another intergenic variant, rs4785426, in close proximity to NKD1 was also inversely associated with ITP (aOR: 0.48, P=1.84x10 -16) . An additional 20 variants met suggestive of genome-wide significance. When comparing sr-ITP and cITP patients, no SNVs (single nucleotide variant) reached genome-wide significance, but one variant, rs117609649, in ABCC4 met suggestive of genome-wide significance (aOR: 0.26, P=4.49x10 -7). Discussion : This is the largest, unbiased genetic study of pediatric ITP patients. The analysis comparing ITP versus healthy controls identified 20 suggestive SNVs and 6 which met genome-wide significance. Several of the top SNVs identified in this study affect Wnt/β-catenin signaling. Wnt-signaling impacts the development and regulation of immune cell populations including dendritic cells, macrophages, NK cells, B cells, and T cells. NAV2 activates Wnt/β-catenin signaling. NAV2 variants have been implicated in autoimmune conditions including Celiac disease and rheumatoid arthritis. NKD1 inhibits the canonical Wnt/β-catenin signaling pathway. The cumulative impact of these variants on Wnt activity in ITP should be evaluated in the future. No genetic variants met genome-wide significance in a comparison of sr-ITP and cITP patients. Collectively, these findings suggest there may be genetic variants implicated in ITP risk, but those genetic features are not specific to sr-ITP or cITP. A focused analysis of 632 genes that cause inborn errors of immunity (IEI) is ongoing. This includes gene burden testing and analysis of pathogenic variants within this gene subset. Variants in IEI genes will also be evaluated in a sub-population of patients with Evans syndrome. Conclusion : ITP is highly heterogenous in its presentation, disease course, and response to therapy. Mirroring its clinical behavior, the genetic contribution to ITP development is complex. This study identified potential SNVs associated with ITP, but not specific to sr-ITP or cITP. Variants in genes that affect the canonical Wnt-signaling pathway may play a role in ITP risk.

Genotype imputation accuracy and the quality metrics of the minor ancestry in multi-ancestry reference panels.

Large-scale imputation reference panels are currently available and have contributed to efficient genome-wide association studies through genotype imputation. However, whether large-size multi-ancestry or small-size population-specific reference panels are the optimal choices for under-represented populations continues to be debated. We imputed genotypes of East Asian (180k Japanese) subjects using the Trans-Omics for Precision Medicine reference panel and found that the standard imputation quality metric (Rsq) overestimated dosage r2 (squared correlation between imputed dosage and true genotype) particularly in marginal-quality bins. Variance component analysis of Rsq revealed that the increased imputed-genotype certainty (dosages closer to 0, 1 or 2) caused upward bias, indicating some systemic bias in the imputation. Through systematic simulations using different template switching rates (θvalue) in the hidden Markov model, we revealed that the lower θ value increased the imputed-genotype certainty and Rsq; however, dosage r2 was insensitive to the θ value, thereby causing a deviation. In simulated reference panels with different sizes and ancestral diversities, the θ value estimates from Minimac decreased with the size of a single ancestry and increased with the ancestral diversity. Thus, Rsq could be deviated from dosage r2 for a subpopulation in the multi-ancestry panel, and the deviation represents different imputed-dosage distributions. Finally, despite the impact of the θ value, distant ancestries in the reference panel contributed only a few additional variants passing a predefined Rsq threshold. We conclude that the θ value substantially impacts the imputed dosage and the imputation quality metric value.

Implementing a Dual-Spectrometer Approach for Improved Surface Reflectance Estimation

Surface reflectance measurement is an integral part of the vicarious calibration of satellite sensors and the validation of satellite-derived top-of-atmosphere (TOA) and surface reflectance products. A well-known practice for estimating surface reflectance is to conduct a field campaign with a spectrometer and a calibration panel, which is labor-intensive and expensive. To address this issue, the Radiometric Calibration Network, RadCalNet, has been developed, which automatically collects surface reflectance over several selected sites. Neither of these approaches can continuously track the atmosphere, which limits their ability to compensate for atmospheric transmittance change during target measurement. This paper presents the dual-spectrometer approach that uses a stationary spectrometer dedicated to continuously tracking changes in atmospheric transmittance by staring at a calibrated reference panel while the mobile spectrometer measures the target. Simultaneous measurement of the reflectance panel and target help to transfer calibration from the stationary spectrometer to the mobile spectrometer and synchronize the measurements. In this manner, atmospheric transmittance changes during target measurement can be tracked and used to reduce the variability of the target surface reflectance. This paper uses field measurement data from combined field campaigns between different calibration groups at Brookings, South Dakota, and Landsat 8 and Landsat 9 underfly efforts over Coconino National Forest, Arizona, and Guymon, Oklahoma. Preliminary results show that even in a clear sky condition, where atmospheric transmittance changes are minimal, the precision of target surface reflectance estimated using the dual-spectrometer approach is 2–6% better than the single-spectrometer approach. The dual-spectrometer approach shows the potential for a substantial improvement in the precision of the target spectral profile when the atmospheric transmittance is changing rapidly during field measurement. Results show that during non-optimal atmospheric conditions, the dual-spectrometer approach improved the precision of the surface reflectance by 50–60% compared to the single-spectrometer approach across most spectral regions. The ability to estimate surface reflectance more precisely using the dual-spectrometer approach in different atmospheric conditions improves the vicarious calibration of optical satellite sensors and the validation of both TOA and surface reflectance products.

Association of APOE Haplotypes With Common Age-Related Ocular Diseases in 412,171 Individuals.

Apolipoprotein E4 (APOE4), a known risk factor for Alzheimer's disease, has controversially been associated with reduced risk of primary open-angle glaucoma (POAG) and age-related macular degeneration (AMD). Here, we sought to systematically quantify the associations of APOE haplotypes with age-related ocular diseases and to assess their scope and age-dependency. We included genetic and registry data from 412,171 Finnish individuals in the FinnGen study. Disease endpoints were defined using nationwide registries. APOE genotypes were directly genotyped using Illumina and Affymetrix arrays or imputed using a custom Finnish reference panel. We evaluated the disease associations of APOE genotypes containing ε2 (without ε4) and ε4 (without ε2) compared with the ε3ε3 genotype using logistic regressions stratified by age. APOE ε4 enriched haplotypes were inversely associated with overall glaucoma (odds ratio [OR] = 0.95, 95% confidence interval [CI] = 0.92-0.99, P = 0.0047), and its subtypes POAG (OR = 0.95, P = 0.027), normal-tension glaucoma (OR = 0.87, P = 0.0058), and suspected glaucoma (OR = 0.95, P = 0.014). Individuals with the ε4 allele also had lower odds for AMD (OR = 0.80, 95% CI = 0.76-0.84, P < 0.001), seen both in dry and neovascular subgroups. A slight negative association was also detected in senile cataract, but this was not reproducible in age-group analyses. Our results support prior evidence of the inverse association of APOE ε4 with glaucoma, but the association was weaker than for AMD. We could not show an association with exfoliation glaucoma, supporting the hypothesis that APOE may be involved in regulating retinal ganglion cell degeneration rather than intraocular pressure.

Multi-ancestry genome-wide association study of cannabis use disorder yields insight into disease biology and public health implications

As recreational use of cannabis is being decriminalized in many places and medical use widely sanctioned, there are growing concerns about increases in cannabis use disorder (CanUD), which is associated with numerous medical comorbidities. Here we performed a genome-wide association study of CanUD in the Million Veteran Program (MVP), followed by meta-analysis in 1,054,365 individuals (ncases = 64,314) from four broad ancestries designated by the reference panel used for assignment (European n = 886,025, African n = 123,208, admixed American n = 38,289 and East Asian n = 6,843). Population-specific methods were applied to calculate single nucleotide polymorphism-based heritability within each ancestry. Statistically significant single nucleotide polymorphism-based heritability for CanUD was observed in all but the smallest population (East Asian). We discovered genome-wide significant loci unique to each ancestry: 22 in European, 2 each in African and East Asian, and 1 in admixed American ancestries. A genetically informed causal relationship analysis indicated a possible effect of genetic liability for CanUD on lung cancer risk, suggesting potential unanticipated future medical and psychiatric public health consequences that require further study to disentangle from other known risk factors such as cigarette smoking.

Retrieving BRDFs from UAV-based radiometers for fiducial reference measurements: caveats and recommendations

Surface Bidirectional reflectance distribution function (BRDF) is a key intrinsic geophysical variable depending only on the characteristics of the observed medium. It is therefore the most suitable measurand to support the definition of fiducial reference measurements (FRM). Field acquisition of surface reflectance data relies on substantial assumptions and simplifications, often without accounting for their impact. For example, the BRDF is a theoretical concept and can never be measured in the field. In contrast, the hemispherical conical reflectance factor (HCRF), which is the measurand obtained during field campaigns, is impacted by all scene elements and is not intrinsic to the surface. This study analyses the impact of four parameters (atmospheric scattering, measurement device field of view cropping, acquisition duration, non-Lambertian reference panels) on HCRF estimation. Simulations are performed on a 3D vegetation scene, using the new radiative transfer model Eradiate. It is found that among the aforementioned parameters, atmospheric scattering alone leads to a relative root-mean-square error (RRMSE) of more than 10% between HCRF and reference Bidirectional reflectance factor (BRF).

Optimal population-specific HLA imputation with dimension reduction.

Human genomics has quickly evolved, powering genome-wide association studies (GWASs). SNP-based GWASs cannot capture the intense polymorphism of HLA genes, highly associated with disease susceptibility. There are methods to statistically impute HLA genotypes from SNP-genotypes data, but lack of diversity in reference panels hinders their performance. We evaluated the accuracy of the 1000 Genomes data as a reference panel for imputing HLA from admixed individuals of African and European ancestries, focusing on (a) the full dataset, (b) 10 replications from 6 populations, and (c) 19 conditions for the custom reference panels. The full dataset outperformed smaller models, with a good F1-score of 0.66 for HLA-B. However, custom models outperformed the multiethnic or population models of similar size (F1-scores up to 0.53, against up to 0.42). We demonstrated the importance of using genetically specific models for imputing populations, which are currently underrepresented in public datasets, opening the door to HLA imputation for every genetic population.