Bayram Cevdet Akdeniz

• Corfield, Elizabeth Claire; Shadrin, Alexey; Frei, Oleksandr; Rahman, Mohammad Zillur; Akdeniz, Bayram Cevdet & Filiz, Tahir Tekin [Vis alle 29 forfattere av denne artikkelen] (2026). Family genetic designs in MoBa provide insights into health and functioning. Nature. ISSN 0028-0836. doi: 10.1038/s41586-026-10926-5. Fulltekst i vitenarkiv Vis sammendrag

  Genome-wide association studies using large, population-based samples of unrelated individuals have discovered thousands of genetic associations with health and disease1. These studies can help explain genetic and environmental risks. However, increasing evidence suggests that population-based estimates, while precise, can also reflect confounding that affects their use and interpretation. This confounding can be overcome using data from genotyped family members, such as nuclear mother–father–child trios2,3. However, samples of genotyped families are rare4,5,6,7,8,9,10,11. Here we illustrate some of the advantages of familial data using the Norwegian Mother, Father and Child Cohort Study (MoBa), a population-based cohort of parents and offspring with extensive genotype data (n ≈ 230,000) (ref. 3), along with broad and longitudinal phenotyping of health and functioning. We provide an overview of MoBa and describe the quality control of genotype data tailored to this extensively related sample. We then use trio data to illustrate how family-based genomic designs can identify distinct direct and indirect sources of genetic influence and structural confounding. As examples, we analyse children’s height, educational achievement, depressive symptoms and sleep duration. These demonstrations highlight MoBa as a broadly valuable resource for advancing understanding of health and functioning across the lifecourse and generations.

• Akdeniz, Bayram Cevdet; Bahrami, Shahram; Hagen, Espen; Fuhrer, Julian; Fominykh, Vera & Shadrin, Alexey [Vis alle 108 forfattere av denne artikkelen] (2026). Polygenic Hazard Score for Predicting Age-associated Risk of Alzheimer’s Disease in European Populations: Development and Validation. medRxiv. doi: 10.1101/2025.07.28.25332293. Fulltekst i vitenarkiv Vis sammendrag

  Abstract Objectives Polygenic hazard score (PHS) models can be used to predict the age-associated risk for complex diseases, including Alzheimer’s disease (AD). In this study, we present an improved PHS model for AD that incorporates a large number of genetic variants and demonstrates enhanced predictive accuracy for age of onset in European populations compared to alternative models. Methods We used the genotyped European Alzheimer & Dementia Biobank (EADB) sample (n=42,120) to develop and evaluate the performance of the PHS model. We developed a PHS model building on 720 genetic variants, including Apolipoprotein E ( APOE ) ε2 and ε4 alleles. We used Elastic Net-regularized Cox regression approach to develop the PHS model. Results The new PHS model (EADB720) improved prediction accuracy compared to alternative models in European populations, with the Odds Ratio OR80/20 from the highest quintile of risk (80th risk percentile and above) to the lowest quintile of risk (20th risk percentile and below) varying between 5.10 and 13.15 within the range of age of onset from 65 – 85 years. Our model also improved risk stratification across ε3/3 individuals of European ancestry (OR80/20 ranges from 1.95 to 3.52). It was also successfully validated in independent datasets (HUSK, DemGene and ADNI) by achieving OR80/20 up to 10.00 in each independent dataset. Conclusion Our EADB720 model significantly improves the accuracy of age-associated risk of AD across European populations (pval<0.03). Accurately predicting the age of onset of AD is of large clinical importance to implementing new AD medication and early intervention in clinical settings.

• Shorter, John R.; Pasman, Joëlle A.; Kurvits, Siim; Jangmo, Andreas; Naamanka, Joonas & Harder, Arvid [Vis alle 31 forfattere av denne artikkelen] (2025). Genome-wide association analyses identify distinct genetic architectures for early-onset and late-onset depression. Nature Genetics. ISSN 1061-4036. 57, s. 2972–2979. doi: 10.1038/s41588-025-02396-8. Fulltekst i vitenarkiv Vis sammendrag

  Major depressive disorder (MDD) is a common and heterogeneous disorder of complex etiology. Studying more homogeneous groups stratified according to clinical characteristics, such as age of onset, can improve the identification of the underlying genetic causes and lead to more targeted treatment strategies. We leveraged Nordic biobanks with longitudinal health registries to investigate differences in the genetic architectures of early-onset (eoMDD; n  = 46,708 cases) and late-onset (loMDD; n  = 37,168 cases) MDD. We identified 12 genomic loci for eoMDD and two for loMDD. Overall, the two MDD subtypes correlated moderately (genetic correlation, r g  = 0.58) and differed in their genetic correlations with related traits. These findings suggest that eoMDD and loMDD have partially distinct genetic signatures, with a specific developmental brain signature for eoMDD. Importantly, we demonstrate that polygenic risk scores (PRS) for eoMDD predict suicide attempts within the first 10 years after the initial diagnosis: the absolute risk for suicide attempt was 26% in the top PRS decile, compared to 12% and 20% in the bottom decile and the intermediate group, respectively. Taken together, our findings can inform precision psychiatry approaches for MDD.

• Frei, Oleksandr; Hindley, Guy; Shadrin, Alexey; Meer, Dennis van der; Akdeniz, Bayram Cevdet & Hagen, Espen [Vis alle 50 forfattere av denne artikkelen] (2024). Improved functional mapping of complex trait heritability with GSA-MiXeR implicates biologically specific gene sets. Nature Genetics. ISSN 1061-4036. 56(6), s. 1310–1318. doi: 10.1038/s41588-024-01771-1. Fulltekst i vitenarkiv
• Akdeniz, Bayram Cevdet; Frei, Oleksandr; Shadrin, Alexey; Vetrov, Dmitry; Kropotov, Dmitry & Hovig, Eivind [Vis alle 8 forfattere av denne artikkelen] (2024). Finemap-MiXeR: A variational Bayesian approach for genetic finemapping. PLoS Genetics. ISSN 1553-7390. 20(8). doi: 10.1371/journal.pgen.1011372. Fulltekst i vitenarkiv Vis sammendrag

  Genome-wide association studies (GWAS) implicate broad genomic loci containing clusters of highly correlated genetic variants. Finemapping techniques can select and prioritize variants within each GWAS locus which are more likely to have a functional influence on the trait. Here, we present a novel method, Finemap-MiXeR, for finemapping causal variants from GWAS summary statistics, controlling for correlation among variants due to linkage disequilibrium. Our method is based on a variational Bayesian approach and direct optimization of the Evidence Lower Bound (ELBO) of the likelihood function derived from the MiXeR model. After obtaining the analytical expression for ELBO’s gradient, we apply Adaptive Moment Estimation (ADAM) algorithm for optimization, allowing us to obtain the posterior causal probability of each variant. Using these posterior causal probabilities, we validated Finemap-MiXeR across a wide range of scenarios using both synthetic data, and real data on height from the UK Biobank. Comparison of Finemap-MiXeR with two existing methods, FINEMAP and SuSiE RSS, demonstrated similar or improved accuracy. Furthermore, our method is computationally efficient in several aspects. For example, unlike many other methods in the literature, its computational complexity does not increase with the number of true causal variants in a locus and it does not require any matrix inversion operation. The mathematical framework of Finemap-MiXeR is flexible and may also be applied to other problems including cross-trait and cross-ancestry finemapping.

• Akdeniz, Bayram Cevdet; Morris, Andrew Hayden; Møller, Pål; Andreassen, Ole A.; Hovig, Eivind & Valentin, Mev Dominguez (2024). Evaluation of a combined model of Polygenic Risk Score and mismatch repair genes in the association of colorectal cancer for Norwegian cohort. Tumori (Milano). ISSN 0300-8916. doi: 10.1177/03008916241303648. Fulltekst i vitenarkiv
• Akdeniz, Bayram Cevdet; Frei, Oleksandr; Hagen, Espen; Filiz, Tahir Tekin; Karthikeyan, Sandeep & Pasman, Joëlle [Vis alle 18 forfattere av denne artikkelen] (2024). COSGAP: COntainerized Statistical Genetics Analysis Pipelines. Bioinformatics Advances. 4(1). doi: 10.1093/bioadv/vbae067. Fulltekst i vitenarkiv Vis sammendrag

  The collection and analysis of sensitive data in large-scale consortia for statistical genetics is hampered by multiple challenges, due to their non-shareable nature. Time-consuming issues in installing software frequently arise due to different operating systems, software dependencies, and limited internet access. For federated analysis across sites, it can be challenging to resolve different problems, including format requirements, data wrangling, setting up analysis on high-performance computing (HPC) facilities, etc. Easier, more standardized, automated protocols and pipelines can be solutions to overcome these issues. We have developed one such solution for statistical genetic data analysis using software container technologies. This solution, named COSGAP: “COntainerized Statistical Genetics Analysis Pipelines,” consists of already established software tools placed into Singularity containers, alongside corresponding code and instructions on how to perform statistical genetic analyses, such as genome-wide association studies, polygenic scoring, LD score regression, Gaussian Mixture Models, and gene-set analysis. Using provided helper scripts written in Python, users can obtain auto-generated scripts to conduct the desired analysis either on HPC facilities or on a personal computer. COSGAP is actively being applied by users from different countries and projects to conduct genetic data analyses without spending much effort on software installation, converting data formats, and other technical requirements.

• Akdeniz, Bayram Cevdet; Mattingsdal, Morten; Dominguez-Valentin, Mev; Frei, Oleksandr; Shadrin, Alexey & Puustusmaa, Mikk [Vis alle 12 forfattere av denne artikkelen] (2023). A Breast Cancer Polygenic Risk Score Is Feasible for Risk Stratification in the Norwegian Population. Cancers. 15(16). doi: 10.3390/cancers15164124. Fulltekst i vitenarkiv Vis sammendrag

  Background: Statistical associations of numerous single nucleotide polymorphisms with breast cancer (BC) have been identified in genome-wide association studies (GWAS). Recent evidence suggests that a Polygenic Risk Score (PRS) can be a useful risk stratification instrument for a BC screening strategy, and a PRS test has been developed for clinical use. The performance of the PRS is yet unknown in the Norwegian population. Aim: To evaluate the performance of PRS models for BC in a Norwegian dataset. Methods: We investigated a sample of 1053 BC cases and 7094 controls from different regions of Norway. PRS values were calculated using four PRS models, and their performance was evaluated by the area under the curve (AUC) and the odds ratio (OR). The effect of the PRS on the age of onset of BC was determined by a Cox regression model, and the lifetime absolute risk of developing BC was calculated using the iCare tool. Results: The best performing PRS model included 3820 SNPs, which yielded an AUC = 0.625 and an OR = 1.567 per one standard deviation increase. The PRS values of the samples correlate with an increased risk of BC, with a hazard ratio of 1.494 per one standard deviation increase (95% confidence interval of 1.406–1.588). The individuals in the highest decile of the PRS have at least twice the risk of developing BC compared to the individuals with a median PRS. The results in this study with Norwegian samples are coherent with the findings in the study conducted using Estonian and UK Biobank samples. Conclusion: The previously validated PRS models have a similar observed accuracy in the Norwegian data as in the UK and Estonian populations. A PRS provides a meaningful association with the age of onset of BC and lifetime risk. Therefore, as suggested in Estonia, a PRS may also be integrated into the screening strategy for BC in Norway.

• Yaylali, Gokberk; Akdeniz, Bayram Cevdet; Tugcu, Tuna & Pusane, Ali Emre (2023). Channel Modeling for Multi-Receiver Molecular Communication Systems. IEEE Transactions on Communications. ISSN 0090-6778. 71(8), s. 4499–4512. doi: 10.1109/TCOMM.2023.3281415. Fulltekst i vitenarkiv
• Usturalı, Umut Eren; Akdeniz, Bayram Cevdet; Tugcu, Tuna & Pusane, Ali Emre (2023). Low-Complexity Timing Methods for Molecular Communication via Diffusion. IEEE Transactions on Molecular, Biological, and Multi-Scale Communications. 9(4), s. 478–482. doi: 10.1109/TMBMC.2023.3305390. Fulltekst i vitenarkiv
• Akdeniz, Bayram Cevdet; Frei, Oleksandr; Shadrin, Alexey; Vetrov, Dmitry; Kropotov, Dmitry & Dale, Anders [Vis alle 8 forfattere av denne artikkelen] (2022). Finemap-MiXeR: A variational Bayesian approach for genetic finemapping. BioRxiv. ISSN 0362-4331. Fulltekst i vitenarkiv
• Akdeniz, Bayram Cevdet; Frei, Oleksandr; Hagen, Espen; Filiz, Tahir Tekin; Karthikeyan, Sandeep & Pasman, Joëlle [Vis alle 18 forfattere av denne artikkelen] (2022). COGEDAP: A COmprehensive GEnomic Data Analysis Platform. arXiv.org. ISSN 2331-8422. Fulltekst i vitenarkiv
• Yetimoglu, Oguzhan; Avci, M.Kerem; Akdeniz, Bayram Cevdet; Yilmaz, H. Birkan; Pusane, Ali E. & Tugcu, Tuna (2021). Multiple transmitter localization via single receiver in 3-D molecular communication via diffusion. Digital signal processing (Print). ISSN 1051-2004. doi: 10.1016/j.dsp.2021.103185. Fulltekst i vitenarkiv
• Oncu, Abdullah Enes; Ozdemir, Halil Umut; Orhan, Halil Ibrahim; Akdeniz, Bayram Cevdet; Toprakci, Asaf & Aslihak, Mehmet Anil [Vis alle 10 forfattere av denne artikkelen] (2021). Analytical investigation of long-time diffusion dynamics in a synaptic channel with glial cells. IEEE Communications Letters. ISSN 1089-7798. 25(11), s. 3444–3448. doi: 10.1109/LCOMM.2021.3105613. Fulltekst i vitenarkiv
• Egan, Malcolm; Akdeniz, Bayram Cevdet & Tang, Bao Quoc (2021). Stochastic reaction and diffusion systems in molecular communications: Recent results and open problems. Digital signal processing (Print). ISSN 1051-2004. doi: 10.1016/j.dsp.2021.103117. Fulltekst i vitenarkiv
• Akdeniz, Bayram Cevdet & Egan, Malcolm (2021). Molecular Communication for Equilibrium State Estimation in Biochemical Processes on a Lab-on-a-Chip. IEEE Transactions on Nanobioscience. ISSN 1536-1241. 20(2), s. 193–201. doi: 10.1109/TNB.2021.3062473. Fulltekst i vitenarkiv
• Egan, Malcolm; Akdeniz, Bayram Cevdet & Tang, Bao Quoc (2021). Equilibrium signaling in spatially inhomogeneous diffusion and external forces. IEEE Transactions on Molecular, Biological, and Multi-Scale Communications. 7(2), s. 106–110. doi: 10.1109/TMBMC.2021.3054908. Fulltekst i vitenarkiv
• Akdeniz, Bayram Cevdet; Egan, Malcolm & Tang, Bao Quoc (2020). Equilibrium Signaling: Molecular Communication Robust to Geometry Uncertainties. IEEE Transactions on Communications. ISSN 0090-6778. 69(2), s. 752–765. doi: 10.1109/TCOMM.2020.3034662. Fulltekst i vitenarkiv
• Akdeniz, Bayram Cevdet & Egan, Malcolm (2020). A Molecular Communication Scheme to Estimate the State of Biochemical Processes on a Lab-on-a-Chip, NanoCoCoA '20: Proceedings of the 1st ACM International Workshop on Nanoscale Computing, Communication, and Applications. Association for Computing Machinery (ACM). ISSN 9781450381161. s. 8–13. doi: 10.1145/3416006.3431272. Fulltekst i vitenarkiv

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• Corfield, Elizabeth Claire; Frei, Oleksandr; Shadrin, Alexey; Rahman, Zillur; Lin, Aihua & Athanasiu, Lavinia [Vis alle 26 forfattere av denne artikkelen] (2022). The Norwegian Mother, Father, and Child cohort study (MoBa) genotyping data resource: the MoBaPsychGen_v1 pipeline. Fulltekst i vitenarkiv
• Corfield, Elizabeth Claire; Shadrin, Alexey; Frei, Oleksandr; Rahman, Zillur; Lin, Aihua & Athanasiu, Lavinia [Vis alle 15 forfattere av denne artikkelen] (2022). Genetic profile of the Norwegian Mother, Father, and Child Cohort Study (MoBa): Results from the MoBaPsychGen pipeline. Fulltekst i vitenarkiv
• Shorter, John; Pasman, Joëlle; Jangmo, Andreas; Kurvits, Siim; Meijsen, Joeri & Frei, Oleksandr [Vis alle 15 forfattere av denne artikkelen] (2022). A LARGE META-ANALYSIS ACROSS FOUR NORDIC COUNTRIES REVEALS SEVERAL SIGNIFICANT GENETIC ASSOCIATIONS FOR EARLY ONSET MAJOR DEPRESSIVE DISORDER. European Neuropsychopharmacology. ISSN 0924-977X. Fulltekst i vitenarkiv
• Pasman, Joëlle; Shorter, John; Jangmo, Andreas; Kurvits, Siim; Meijsen, Joeri & Frei, Oleksandr [Vis alle 13 forfattere av denne artikkelen] (2022). IS GENETIC RISK FOR EARLY ONSET MAJOR DEPRESSIVE DISORDER ASSOCIATED WITH MORE SEVERE CLINICAL FEATURES THAN BROAD MAJOR DEPRESSIVE DISORDER? European Neuropsychopharmacology. ISSN 0924-977X. Fulltekst i vitenarkiv
• Akdeniz, Bayram Cevdet; Mattingsdal, Morten; Valentin, Mev Dominguez; Frei, Oleksandr; Shadrin, Alexey & Puustusmaa, Mikk [Vis alle 11 forfattere av denne artikkelen] (2022). Implementation of polygenic risk score guided breast cancer prediction in Norwegian data. NSHG-PM 2022. Fulltekst i vitenarkiv
• Akdeniz, Bayram Cevdet; Bøen, Rune; Frei, Oleksandr; Hovig, Eivind; Andreassen, Ole & Sønderby, Ida Elken (2022). LARGE-SCALE ANALYSIS WITH SOFTWARE CONTAINERS IN ENIGMA-CNV–AN INTERNATIONAL WORKING GROUP TO STUDY RECURRENT COPY NUMBER VARIANTS AND BRAIN MEASURES. Neuropsychopharmacology, 2022. Fulltekst i vitenarkiv
• Corfield, Elizabeth Claire; Frei, Oleksandr; Shadrin, Alexey; Rahman, Zillur; Lin, Aihua & Athanasiu, Lavinia [Vis alle 26 forfattere av denne artikkelen] (2022). The Norwegian Mother, Father, and Child cohort study (MoBa) genotyping data resource: MoBaPsychGen pipeline v.1. Cold Spring Harbor Laboratory Press (CSHL). doi: 10.1101/2022.06.23.496289. Fulltekst i vitenarkiv Vis sammendrag

  Background: The Norwegian Mother, Father, and Child Cohort Study (MoBa) is a population-based pregnancy cohort, which includes approximately 114,500 children, 95,200 mothers, and 75,200 fathers. Genotyping of MoBa has been conducted through multiple research projects, spanning several years; using varying selection criteria, genotyping arrays, and genotyping centres. MoBa contains numerous interrelated families, which necessitated the implementation of a family-based quality control (QC) pipeline that verifies and accounts for diverse types of relatedness. Methods: The MoBaPsychGen pipeline, comprising pre-imputation QC, phasing, imputation, and post-imputation QC, was developed based on current best-practice protocols and implemented to account for the complex structure of the MoBa genotype data. The pipeline includes QC on both single nucleotide polymorphism (SNP) and individual level. Phasing and imputation were performed using the publicly available Haplotype Reference Consortium release 1.1 panel as a reference. Information from the Medical Birth Registry of Norway and MoBa questionnaires were used to identify biological sex, year of birth, reported parent-offspring (PO) relationships, and multiple births (only available in the offspring generation). Results: In total, 207,569 unique individuals (90% of the unique individuals included in the study) and 6,981,748 SNPs passed the MoBaPsychGen pipeline. The relatedness checks performed throughout the pipeline allowed identification of within-generation and across-generation first-degree, second-degree, and third-degree relatives. The individuals passing post-imputation QC comprised 64,471 families ranging in size from singletons to 84 unique individuals (singletons are included as families as other family members may not have been genotyped, imputed, or passed post-imputation QC). The relationships identified include 287 monozygotic twin pairs, 22,884 full siblings, 117,004 PO pairs, 23,299 second-degree relative pairs, and 10,828 third-degree relative pairs. Discussion: MoBa contains a highly complex relatedness structure, with a variety of family structures including singletons, PO duos, full (mother, father, child) PO trios, nuclear families, blended families, and extended families. The availability of robustly quality-controlled genetic data for such a large cohort with a unique extended family structure will allow many novel research questions to be addressed. Furthermore, the MoBaPsychGen pipeline has potential utility in similar cohorts.

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