Cyclic block filtered multitone modulation

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Prognostic Prediction of Genotype vs Phenotype in Genetic Cardiomyopathies

Background: Diverse genetic backgrounds often lead to phenotypic heterogeneity in cardiomyopathies (CMPs). Previous genotype-phenotype studies have primarily focused on the analysis of a single phenotype, and the diagnostic and prognostic features of the CMP genotype across different phenotypic expressions remain poorly understood. Objectives: We sought to define differences in outcome prediction when stratifying patients based on phenotype at presentation compared with genotype in a large cohort of patients with CMPs and positive genetic testing. Methods: Dilated cardiomyopathy (DCM), arrhythmogenic right ventricular cardiomyopathy, left-dominant arrhythmogenic cardiomyopathy, and biventricular arrhythmogenic cardiomyopathy were examined in this study. A total of 281 patients (80% DCM) with pathogenic or likely pathogenic variants were included. The primary and secondary outcomes were: 1) all-cause mortality (D)/heart transplant (HT); 2) sudden cardiac death/major ventricular arrhythmias (SCD/MVA); and 3) heart failure-related death (DHF)/HT/left ventricular assist device implantation (LVAD). Results: Survival analysis revealed that SCD/MVA events occurred more frequently in patients without a DCM phenotype and in carriers of DSP, PKP2, LMNA, and FLNC variants. However, after adjustment for age and sex, genotype-based classification, but not phenotype-based classification, was predictive of SCD/MVA. LMNA showed the worst trends in terms of D/HT and DHF/HT/LVAD. Conclusions: Genotypes were associated with significant phenotypic heterogeneity in genetic cardiomyopathies. Nevertheless, in our study, genotypic-based classification showed higher precision in predicting the outcome of patients with CMP than phenotype-based classification. These findings add to our current understanding of inherited CMPs and contribute to the risk stratification of patients with positive genetic testing

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Publisher Copyright: © 2022, The Author(s).Background: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.Peer reviewe

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Funding GMP, PN, and CW are supported by NHLBI R01HL127564. GMP and PN are supported by R01HL142711. AG acknowledge support from the Wellcome Trust (201543/B/16/Z), European Union Seventh Framework Programme FP7/2007–2013 under grant agreement no. HEALTH-F2-2013–601456 (CVGenes@Target) & the TriPartite Immunometabolism Consortium [TrIC]-Novo Nordisk Foundation’s Grant number NNF15CC0018486. JMM is supported by American Diabetes Association Innovative and Clinical Translational Award 1–19-ICTS-068. SR was supported by the Academy of Finland Center of Excellence in Complex Disease Genetics (Grant No 312062), the Finnish Foundation for Cardiovascular Research, the Sigrid Juselius Foundation, and University of Helsinki HiLIFE Fellow and Grand Challenge grants. EW was supported by the Finnish innovation fund Sitra (EW) and Finska Läkaresällskapet. CNS was supported by American Heart Association Postdoctoral Fellowships 15POST24470131 and 17POST33650016. Charles N Rotimi is supported by Z01HG200362. Zhe Wang, Michael H Preuss, and Ruth JF Loos are supported by R01HL142302. NJT is a Wellcome Trust Investigator (202802/Z/16/Z), is the PI of the Avon Longitudinal Study of Parents and Children (MRC & WT 217065/Z/19/Z), is supported by the University of Bristol NIHR Biomedical Research Centre (BRC-1215–2001) and the MRC Integrative Epidemiology Unit (MC_UU_00011), and works within the CRUK Integrative Cancer Epidemiology Programme (C18281/A19169). Ruth E Mitchell is a member of the MRC Integrative Epidemiology Unit at the University of Bristol funded by the MRC (MC_UU_00011/1). Simon Haworth is supported by the UK National Institute for Health Research Academic Clinical Fellowship. Paul S. de Vries was supported by American Heart Association grant number 18CDA34110116. Julia Ramierz acknowledges support by the People Programme of the European Union’s Seventh Framework Programme grant n° 608765 and Marie Sklodowska-Curie grant n° 786833. Maria Sabater-Lleal is supported by a Miguel Servet contract from the ISCIII Spanish Health Institute (CP17/00142) and co-financed by the European Social Fund. Jian Yang is funded by the Westlake Education Foundation. Olga Giannakopoulou has received funding from the British Heart Foundation (BHF) (FS/14/66/3129). CHARGE Consortium cohorts were supported by R01HL105756. Study-specific acknowledgements are available in the Additional file 32: Supplementary Note. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services.Peer reviewedPublisher PD

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Abstract Background Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis.

BACKGROUND: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. RESULTS: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3-5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. CONCLUSIONS: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Funding Information: GMP, PN, and CW are supported by NHLBI R01HL127564. GMP and PN are supported by R01HL142711. AG acknowledge support from the Wellcome Trust (201543/B/16/Z), European Union Seventh Framework Programme FP7/2007–2013 under grant agreement no. HEALTH-F2-2013–601456 (CVGenes@Target) & the TriPartite Immunometabolism Consortium [TrIC]-Novo Nordisk Foundation’s Grant number NNF15CC0018486. JMM is supported by American Diabetes Association Innovative and Clinical Translational Award 1–19-ICTS-068. SR was supported by the Academy of Finland Center of Excellence in Complex Disease Genetics (Grant No 312062), the Finnish Foundation for Cardiovascular Research, the Sigrid Juselius Foundation, and University of Helsinki HiLIFE Fellow and Grand Challenge grants. EW was supported by the Finnish innovation fund Sitra (EW) and Finska Läkaresällskapet. CNS was supported by American Heart Association Postdoctoral Fellowships 15POST24470131 and 17POST33650016. Charles N Rotimi is supported by Z01HG200362. Zhe Wang, Michael H Preuss, and Ruth JF Loos are supported by R01HL142302. NJT is a Wellcome Trust Investigator (202802/Z/16/Z), is the PI of the Avon Longitudinal Study of Parents and Children (MRC & WT 217065/Z/19/Z), is supported by the University of Bristol NIHR Biomedical Research Centre (BRC-1215–2001) and the MRC Integrative Epidemiology Unit (MC_UU_00011), and works within the CRUK Integrative Cancer Epidemiology Programme (C18281/A19169). Ruth E Mitchell is a member of the MRC Integrative Epidemiology Unit at the University of Bristol funded by the MRC (MC_UU_00011/1). Simon Haworth is supported by the UK National Institute for Health Research Academic Clinical Fellowship. Paul S. de Vries was supported by American Heart Association grant number 18CDA34110116. Julia Ramierz acknowledges support by the People Programme of the European Union’s Seventh Framework Programme grant n° 608765 and Marie Sklodowska-Curie grant n° 786833. Maria Sabater-Lleal is supported by a Miguel Servet contract from the ISCIII Spanish Health Institute (CP17/00142) and co-financed by the European Social Fund. Jian Yang is funded by the Westlake Education Foundation. Olga Giannakopoulou has received funding from the British Heart Foundation (BHF) (FS/14/66/3129). CHARGE Consortium cohorts were supported by R01HL105756. Study-specific acknowledgements are available in the Additional file : Supplementary Note. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services. Publisher Copyright: © 2022, The Author(s).Background: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.Peer reviewe

Cyclic Block Filtered Multitone Modulation: Design and Performance Analysis

Nowadays, high data rate communication demand is growing. Thus, several communication technologies, both wireless and wireline, have adopted Filter Bank Modulation (FBM) at the physical layer. In a general FBM scheme, the high data rate stream is converted into a series of several parallel low data rate streams. These streams are modulated with a series of carrier signals. In frequency domain, the available bandwidth is partitioned in disjointed sub-channels. If the sub-channel number is sufficiently high, the sub-channel frequency response is quasi-flat and the equalizer can be simplified. Furthermore, FBM schemes have low complexity digital implementation and bit loading could be used to minimize the transmission power. In this thesis, a FBM transceiver is presented. The idea is to obtain good sub-channel frequency confinement as it is done by the family of exponentially modulated filter banks that is typically referred to as Filtered Multitone (FMT) modulation. However, differently from conventional FMT, the linear convolutions are replaced with circular convolutions. Since transmission occurs in blocks, the scheme is referred to as Cylic Block Filtered Multitone Modulation (CB-FMT). This thesis focuses on the principles, design, implementation and performances analysis of CB-FMT. In particular, it is shown that an efficient realization of both the transmitter and the receiver is possible in the frequency domain (FD), and it is based on the concatenation of an inner Discrete Fourier Transform (DFT) and a bank of outer DFTs. Such an implementation suggests a simple sub-channel FD equalizer. The overall required implementation complexity is lower than in FMT. Furthermore, the orthogonal filter bank design is simplified. The sub-channel frequency confinement in CB-FMT yields compact power spectrum and lower peak-to-average power ratio than in Orthogonal Frequency Division Multiplexing (OFDM). Then, the orthogonal prototype pulse design problem is considered. The orthogonality conditions are derived in time domain and frequency domain. These conditions are translated in matrix form and pulse coefficients are parameterized with hyper-spherical coordinates, a non-linear combination of trigonometric functions. The mathematical analysis shows that exists an infinite number of solutions. Next, the orthogonality is discussed in presence of a transmission medium. In general, the channel could destroy the orthogonality. Finally, optimal orthogonal pulses are designed to maximize the in-band-toout- band energy ratio and the achievable rate in time-variant channel scenario. These optimal pulses improve the performance of the baseline root-raisedcosine pulse. Furthermore, the equalization task is discussed. Equalizers are necessary to restore the orthogonality when an equivalent filter is inserted between the transmitter and the receiver. This filter could represent the transmission medium, a real interpolation filter or the hardware non-ideality. We discuss several equalizers, both for time-invariant and time-variant channels. A cyclic prefix (CP) can be added to the transmitted signal. We show that when the CP length is greater than the channel impulse response length, perfect reconstruction (PR) is possible. For time-invariant channels, a simple 1-tap equalizer is sufficient to restore the orthogonality. We show that in the time-variant scenario, the 1-tap equalizer is not sufficient to restore the orthogonality. Several equalizers are proposed for the time-variant case. Finally, performances in real application scenarios are evaluated. We start from Power Line Communications. For in-home high data rate communications, broadband PLC (BB-PLC) is used. BB-PLC generally operates in the band 2-30 MHz. Transmission above 30 MHz is possible, but the electromagnetic compatibility (EMC) limits are more stringent than the limits in the band below 30 MHz. In the 2-30 MHz range there are several sub-bands dedicated to other communication systems, e.g. to amateur radio. A spectrum notching mask has to be fulfilled by the power spectral density (PSD) of the transmitted signal to grant coexistence. For command and control applications, narrowband PLC (NB-PLC) is used. NB-PLC operates in portions of the 3-500 kHz spectrum and it has to obey certain spectral masks for EMC and coexistence issues, similarly to BB-PLC. Although OFDM allows simple spectrum management by switching on-off the sub-channels, its poor sub-channel frequency selectivity translates into a poor spectrum usage. An agile use of the spectrum and higher spectral efficiency can be obtained with filter bank modulation. In particular, we investigate the use of CB-FMT modulation and compare it to pulse-shaped OFDM (PS-OFDM) deployed in the G3-PLC and IEEE P1901.2 standards for NB-PLC. For BB-PLC, we compare CB-FMT with the HomePlug standard. The comparison shows that higher spectral efficiency and improved spectrum management can be achieved with CB-FMT. For the wireless scenario, the land mobile radio systems are considered. The transmitted signal propagates through a multipath channel. This propagation model is caused by several natural and man-made obstacles that introduce reflections, diffraction and scattering. Time-invariant and time-variant scenarios are considered. The FD equalization allows the exploitation of the transmission medium time and frequency diversity; thus, it potentially yields lower symbol error rate and higher achievable rate in time-variant frequency-selective fading