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Association of blood-based transcriptional risk scores with biomarkers for Alzheimer disease.

ABSTRACT: Objective:To determine whether transcriptional risk scores (TRSs), a summation of polarized expression levels of functional genes, reflect the risk of Alzheimer disease (AD). Methods:Blood transcriptome data were from Caucasian participants, which included AD, mild cognitive impairment, and cognitively normal controls (CN) in the Alzheimer's Disease Neuroimaging Initiative (ADNI, n = 661) and AddNeuroMed (n = 674) cohorts. To calculate TRSs, we selected functional genes that were expressed under the control of the AD risk loci and were identified as being responsible for AD by using Bayesian colocalization and mendelian randomization methods. Regression was used to investigate the association of the TRS with diagnosis (AD vs CN) and MRI biomarkers (entorhinal thickness and hippocampal volume). Regression was also used to evaluate whether expression of each functional gene was associated with AD diagnosis. Results:The TRS was significantly associated with AD diagnosis, hippocampal volume, and entorhinal cortical thickness in the ADNI. The association of the TRS with AD diagnosis and entorhinal cortical thickness was also replicated in AddNeuroMed. Among functional genes identified to calculate the TRS, CD33 and PILRA were significantly upregulated, and TRAPPC6A was significantly downregulated in patients with AD compared with CN, all of which were identified in the ADNI and replicated in AddNeuroMed. Conclusions:The blood-based TRS is significantly associated with AD diagnosis and neuroimaging biomarkers. In blood, CD33 and PILRA were known to be associated with uptake of ?-amyloid and herpes simplex virus 1 infection, respectively, both of which may play a role in the pathogenesis of AD. Classification of evidence:The study is rated Class III because of the case control design and the risk of spectrum bias.

SUBMITTER: Park YH

PROVIDER: S-EPMC7577551 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Association of blood-based transcriptional risk scores with biomarkers for Alzheimer disease.

Park Young Ho YH Hodges Angela A Simmons Andrew A Lovestone Simon S Weiner Michael W MW Kim SangYun S Saykin Andrew J AJ Nho Kwangsik K

Neurology. Genetics 20200930 6

<h4>Objective</h4>To determine whether transcriptional risk scores (TRSs), a summation of polarized expression levels of functional genes, reflect the risk of Alzheimer disease (AD).<h4>Methods</h4>Blood transcriptome data were from Caucasian participants, which included AD, mild cognitive impairment, and cognitively normal controls (CN) in the Alzheimer's Disease Neuroimaging Initiative (ADNI, n = 661) and AddNeuroMed (n = 674) cohorts. To calculate TRSs, we selected functional genes that were ...[more]

PMID: 33134515

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Project description:Background and objectiveBlood biomarkers for Alzheimer disease (AD) have consistently proven to be associated with CSF or PET biomarkers and effectively discriminate AD from other neurodegenerative diseases. Our aim was to test their utility in clinical practice, from a multicentric unselected prospective cohort where patients presented with a large spectrum of cognitive deficits or complaints.MethodsThe MEMENTO cohort enrolled 2,323 outpatients with subjective cognitive complaint (SCC) or mild cognitive impairment (MCI) consulting in 26 French memory clinics. Participants had neuropsychological assessments, MRI, and blood sampling at baseline. CSF sampling and amyloid PET were optional. Baseline blood Aβ42/40 ratio, total tau, p181-tau, and neurofilament light chain (NfL) were measured using a Simoa HD-X analyzer. An expert committee validated incident dementia cases during a 5-year follow-up period.ResultsOverall, 2,277 individuals had at least 1 baseline blood biomarker available (n = 357 for CSF subsample, n = 649 for PET subsample), among whom 257 were diagnosed with clinical AD/mixed dementia during follow-up. All blood biomarkers but total tau were mildly correlated with their equivalence in the CSF (r = 0.33 to 0.46, p < 0.0001) and were associated with amyloid-PET status (p < 0.0001). Blood p181-tau was the best blood biomarker to identify amyloid-PET positivity (area under the curve = 0.74 [95% CI = 0.69; 0.79]). Higher blood and CSF p181-tau and NfL concentrations were associated with accelerated time to AD dementia onset with similar incidence rates, whereas blood Aβ42/40 was less efficient than CSF Aβ42/40. Blood p181-tau alone was the best blood predictor of 5-year AD/mixed dementia risk (c-index = 0.73 [95% CI = 0.69; 0.77]); its accuracy was higher in patients with clinical dementia rating (CDR) = 0 (c-index = 0.83 [95% CI = 0.69; 0.97]) than in patients with CDR = 0.5 (c-index = 0.70 [95% CI = 0.66; 0.74]). A "clinical" reference model (combining demographics and neuropsychological assessment) predicted AD/mixed dementia risk with a c-index = 0.88 [95% CI = 0.86-0.91] and performance increased to 0.90 [95% CI = 0.88; 0.92] when adding blood p181-tau + Aβ42/40. A "research" reference model (clinical model + apolipoprotein E genotype and AD signature on MRI) had a c-index = 0.91 [95% CI = 0.89-0.93] increasing to 0.92 [95% CI = 0.90; 0.93] when adding blood p181-tau + Aβ42/40. Chronic kidney disease and vascular comorbidities did not affect predictive performances.DiscussionIn a clinic-based cohort of patients with SCC or MCI, blood biomarkers may be good hallmarks of underlying pathology but add little to 5-year dementia risk prediction models including traditional predictors.

Project description:Short-term memory dysfunction is a key early feature of Alzheimer's disease (AD). Psychiatric patients may be at higher risk for memory dysfunction and subsequent AD due to the negative effects of stress and depression on the brain. We carried out longitudinal within-subject studies in male and female psychiatric patients to discover blood gene expression biomarkers that track short term memory as measured by the retention measure in the Hopkins Verbal Learning Test. These biomarkers were subsequently prioritized with a convergent functional genomics approach using previous evidence in the field implicating them in AD. The top candidate biomarkers were then tested in an independent cohort for ability to predict state short-term memory, and trait future positive neuropsychological testing for cognitive impairment. The best overall evidence was for a series of new, as well as some previously known genes, which are now newly shown to have functional evidence in humans as blood biomarkers: RAB7A, NPC2, TGFB1, GAP43, ARSB, PER1, GUSB, and MAPT. Additional top blood biomarkers include GSK3B, PTGS2, APOE, BACE1, PSEN1, and TREM2, well known genes implicated in AD by previous brain and genetic studies, in humans and animal models, which serve as reassuring de facto positive controls for our whole-genome gene expression discovery approach. Biological pathway analyses implicate LXR/RXR activation, neuroinflammation, atherosclerosis signaling, and amyloid processing. Co-directionality of expression data provide new mechanistic insights that are consistent with a compensatory/scarring scenario for brain pathological changes. A majority of top biomarkers also have evidence for involvement in other psychiatric disorders, particularly stress, providing a molecular basis for clinical co-morbidity and for stress as an early precipitant/risk factor. Some of them are modulated by existing drugs, such as antidepressants, lithium and omega-3 fatty acids. Other drug and nutraceutical leads were identified through bioinformatic drug repurposing analyses (such as pioglitazone, levonorgestrel, salsolidine, ginkgolide A, and icariin). Our work contributes to the overall pathophysiological understanding of memory disorders and AD. It also opens new avenues for precision medicine- diagnostics (assement of risk) as well as early treatment (pharmacogenomically informed, personalized, and preventive).

Project description:ImportancePrevious research has suggested an association of kidney function with risk of Alzheimer disease (AD) or other dementias and dementia-related blood biomarkers, but a distinct association remains unclear.ObjectiveTo evaluate the association of kidney function with risk of diagnosis of incident AD or dementia within 17 years and with the blood biomarkers neurofilament light (NfL), phosphorylated tau181 (p-tau181), and glial fibrillary acidic protein (GFAP).Design, setting, and participantsIn this prospective, population-based cohort study and nested case-control study, 9940 participants in Germany were enrolled between 2000 and 2002 by their general practitioners and followed up for up to 17 years. Participants were included if information on dementia status and creatinine/cystatin C measurements were available. A subsample of participants additionally had measurements of NfL, p-tau181, and GFAP obtained from blood samples. Statistical analysis was performed from January 3 to November 25, 2022.ExposuresImpaired kidney function, based on estimated glomerular filtration rate less than 60 mL/min/1.73 m2 according to the 2021 Chronic Kidney Disease Epidemiology Collaboration creatinine-cystatin C equation.Main outcomes and measuresAll-cause dementia, AD, and vascular dementia diagnosis, as well as log-transformed levels of NfL, p-tau181, and GFAP in blood.ResultsOf 6256 participants (3402 women [54.4%]; mean [SD] age at baseline, 61.7 [6.6] years), 510 received an all-cause dementia diagnosis within 17 years of baseline. The dementia-related blood biomarker nested case-control sample included 766 participants. After adjusting for age and sex, impaired kidney function at baseline was not associated with a higher risk of all-cause dementia (hazard ratio [HR], 0.95; 95% CI, 0.69-1.29), AD (HR, 0.94; 95% CI, 0.55-1.63), or vascular dementia diagnosis (HR, 1.06; 95% CI, 0.65-1.70) within 17 years. In the cross-sectional analysis, after adjusting for age and sex, impaired kidney function was significantly associated with NfL and p-tau181 levels in blood (NfL: β = 0.47 and P < .001; p-tau181: β = 0.21 and P = .003). After adjusting for age and sex, significant associations with GFAP levels were evident only among men (men: β = 0.31 and P = .006; women: β = -0.12 and P = .11).Conclusions and relevanceIn this population-based study of community-dwelling adults, reduced kidney function was associated with increased levels of dementia-related blood biomarkers but not increased dementia risk. Kidney function might influence the accuracy of dementia-related blood biomarkers and should be considered in clinical translation.

Project description:BackgroundA relevant part of the genetic architecture of complex traits is still unknown; despite the discovery of many disease-associated common variants. Polygenic risk score (PRS) models are based on the evaluation of the additive effects attributable to common variants and have been successfully implemented to assess the genetic susceptibility for many phenotypes. In contrast, burden tests are often used to identify an enrichment of rare deleterious variants in specific genes. Both kinds of genetic contributions are typically analyzed independently. Many studies suggest that complex phenotypes are influenced by both low effect common variants and high effect rare deleterious variants. The aim of this paper is to integrate the effect of both common and rare functional variants for a more comprehensive genetic risk modeling.MethodsWe developed a framework combining gene-based scores based on the enrichment of rare functionally relevant variants with genome-wide PRS based on common variants for association analysis and prediction models. We applied our framework on UK Biobank dataset with genotyping and exome data and considered 28 blood biomarkers levels as target phenotypes. For each biomarker, an association analysis was performed on full cohort using gene-based scores (GBS). The cohort was then split into 3 subsets for PRS construction and feature selection, predictive model training, and independent evaluation, respectively. Prediction models were generated including either PRS, GBS or both (combined).ResultsAssociation analyses of the cohort were able to detect significant genes that were previously known to be associated with different biomarkers. Interestingly, the analyses also revealed heterogeneous effect sizes and directionality highlighting the complexity of the blood biomarkers regulation. However, the combined models for many biomarkers show little or no improvement in prediction accuracy compared to the PRS models.ConclusionThis study shows that rare variants play an important role in the genetic architecture of complex multifactorial traits such as blood biomarkers. However, while rare deleterious variants play a strong role at an individual level, our results indicate that classical common variant based PRS might be more informative to predict the genetic susceptibility at the population level.

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Association of blood-based transcriptional risk scores with biomarkers for Alzheimer disease.

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Association of blood-based transcriptional risk scores with biomarkers for Alzheimer disease.

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