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Biology subjects

Ilkov, M.

Publications and source records attributed to Ilkov, M..

5 recordsLinked to original sources

Single-Nuclei Transcriptomic Characterization of APOE4-Associated Alzheimer's Disease

Apolipoprotein E (APOE) genotype contributes significantly to Alzheimers disease (AD) risk and pathogenesis. Cell-type specific effects of APOE alleles have been studied. However, due to the variable prevalence of APOE genotypes within human populations, characterization of cell-type specific transcriptomes across APOE genotypes has been challenging. Here, we integrated previous and newly generated single-nuclei sequencing (snRNA-seq) data in the prefrontal cortex (PFC) from individuals across APOE genotypes (2/2, 2/3, 3/3, 3/4, 4/4). Clustering analysis revealed distinct excitatory and microglial subpopulations that were uniquely enriched or depleted for APOE4/4 AD. Notably, an excitatory neuronal cluster exhibited neurofibrillary tangle (NFT) signatures and was selectively depleted in APOE4/4 AD cases. In addition, several microglial subpopulations were influenced by both APOE4 dosage and disease status. Among these, the putative AD risk gene FRMD4A emerged as APOE4 dose and AD-dependent. These findings were validated by RNAscope in an extended cohort. Together, our findings provide insights into how APOE4 reshapes cellular states and contributes to cell-type-specific vulnerability in AD.

neuroscience↗

Multi-ancestry genome-wide gene-sleep interactions identify novel loci for blood pressure

Long and short sleep duration are associated with elevated blood pressure (BP), possibly through effects on molecular pathways that influence neuroendocrine and vascular systems. To gain new insights into the genetic basis of sleep-related BP variation, we performed genome-wide gene by short or long sleep duration interaction analyses on four BP traits (systolic BP, diastolic BP, mean arterial pressure, and pulse pressure) across five ancestry groups using 1 degree of freedom (1df) interaction and 2df joint tests. Primary multi-ancestry analyses in 62,969 individuals in stage 1 identified 3 novel loci that were replicated in an additional 59,296 individuals in stage 2, including rs7955964 (FIGNL2/ANKRD33) showing significant 1df interactions with long sleep duration and rs73493041 (SNORA26/C9orf170) and rs10406644 (KCTD15/LSM14A) showing significant 1df interactions with short sleep duration (Pint < 5x10-8). Secondary ancestry-specific two-stage analyses and combined stage 1 and 2 analyses additionally identified 23 novel loci that need external replication, including 3 and 5 loci showing significant 1df interactions with long and short sleep duration, respectively (Pint < 5x10-8). Multiple genes mapped to our 26 novel loci have known functions in sleep-wake regulation, nervous and cardiometabolic systems. We also identified new gene by long sleep interactions near five known BP loci ([&le;]1Mb) including NME7, FAM208A, MKLN1, CEP164, and RGL3/ELAVL3 (Pint < 5x10-8). This study indicates that sleep and primary mechanisms regulating BP may interact to elevate BP level, suggesting novel insights into sleep-related BP regulation.

genomics↗

Human serum proteome profoundly overlaps with genetic signatures of disease

Circulating proteins are prognostic for human outcomes including cancer, heart failure, brain trauma and brain amyloid plaque burden. A deep serum proteome survey recently revealed close associations of serum protein networks and common diseases. The present study reveals unprecedented number of individual serum proteins that overlap genetic signatures of diseases emanating from different tissues of the body. Here, 54,469 low-frequency and common exome-array variants were compared with 4782 protein measurements in the serum of 5343 individuals of the deeply annotated AGES Reykjavik cohort. Using a study-wide significant threshold, 2019 independent exome array variants affecting levels of 2135 serum proteins were identified. These variants overlapped genetic loci for hundreds of complex disease traits, emphasizing the emerging role for serum proteins as biomarkers of and potential causative agents of multiple diseases.

genetics↗

Deep serum proteomics reveal biomarkers and causal candidates for type 2 diabetes

The prevalence of type 2 diabetes mellitus (T2DM) is expected to increase rapidly in the next decades, posing a major challenge to societies worldwide. The emerging era of precision medicine calls for the discovery of biomarkers of clinical value for prediction of disease onset, where causal biomarkers can furthermore provide actionable targets. Blood-based factors like serum proteins are in contact with every organ in the body to mediate global homeostasis and may thus directly regulate complex processes such as aging and the development of common chronic diseases. We applied a data-driven proteomics approach measuring serum levels of 4,137 proteins in 5,438 Icelanders to discover novel biomarkers for incident T2DM and describe the serum protein profile of prevalent T2DM. We identified 536 proteins associated with incident or prevalent T2DM. Through LASSO penalized logistic regression analysis combined with bootstrap resampling, a panel of 20 protein biomarkers that accurately predicted incident T2DM was identified with a significant incremental improvement over traditional risk factors. Finally, a Mendelian randomization analysis provided support for a causal role of 48 proteins in the development of T2DM, which could be of particular interest as novel therapeutic targets.

genetics↗

Multi-ancestry analysis of gene-sleep interactions in 126,926 individuals identifies multiple novel blood lipid loci that contribute to our understanding of sleep-associated adverse blood lipid profile

Both short and long sleep are associated with an adverse lipid profile, likely through different biological pathways. To provide new insights in the biology of sleep-associated adverse lipid profile, we conducted multi-ancestry genome-wide sleep-SNP interaction analyses on three lipid traits (HDL-c, LDL-c and triglycerides). In the total study sample (discovery + replication) of 126,926 individuals from 5 different ancestry groups, when considering either long or short total sleep time interactions in joint analyses, we identified 49 novel lipid loci, and 10 additional novel lipid loci in a restricted sample of European-ancestry cohorts. In addition, we identified new gene-sleep interactions for known lipid loci such as LPL and PCSK9. The novel gene-sleep interactions had a modest explained variance in lipid levels: most notable, gene-short-sleep interactions explained 4.25% of the variance in triglyceride concentration. Collectively, these findings contribute to our understanding of the biological mechanisms involved in sleep-associated adverse lipid profiles.

genomics↗