Off-label higher doses of serotonin reuptake inhibitors in the treatment of obsessive-compulsive disorder: Safety and tolerability.

OBJECTIVE: To examine the long-term safety and tolerability of off-label high-dose serotonin reuptake inhibitors (OLHD-SRIs) in the treatment of obsessive-compulsive disorder (OCD). METHODS: A retrospective longitudinal study was performed on 105 randomly selected outpatients diagnosed with OCD and were treated with OLHD-SRIs for at least 6 months. Patients received sertraline >200 mg/day, escitalopram >20 mg/day, fluvoxamine >300 mg/day, and fluoxetine >60 mg/day, combined with exposure and response prevention therapy. Patients were divided into three dosing groups: sertraline equivalent dose (SED) ≤ 200 mg/day (n = 26, 24.7%), 201-400 mg/day (n = 51, 48.5%) and 401-650 mg/day (n = 28, 26.6%). Safety and tolerability were assessed with an electrocardiogram, blood biochemistry, complete blood count, and side-effects monitoring. RESULTS: SED ranged from 100 to 650 mg/day and the mean duration of OLHD-SRI treatment was 20.8 months. The most common side-effects reported were sexual dysfunction (n = 36, 34%), weight gain (n = 28, 27%), sedation (n = 27, 26%), hyperhidrosis (n = 20, 19%), and tremor (n = 11, 10%). Abnormal ECG was documented in one patient, and another patient experienced a first-time seizure, whereas elevated liver enzymes were seen in 4.8% of the sample (n = 5). None of the patients had serotonin syndrome or drug-induced liver injury. Side-effects did not differ among the three dosing groups. CONCLUSION: OLHD-SRIs appear to be safe and well tolerated in OCD patients in SED ≤ 650 mg/day doses and the side-effects did not differ between the three dosing groups.

Determinants of mosaic chromosomal alteration fitness.

Clonal hematopoiesis (CH) is characterized by the acquisition of a somatic mutation in a hematopoietic stem cell that results in a clonal expansion. These driver mutations can be single nucleotide variants in cancer driver genes or larger structural rearrangements called mosaic chromosomal alterations (mCAs). The factors that influence the variations in mCA fitness and ultimately result in different clonal expansion rates are not well understood. We used the Passenger-Approximated Clonal Expansion Rate (PACER) method to estimate clonal expansion rate as PACER scores for 6,381 individuals in the NHLBI TOPMed cohort with gain, loss, and copy-neutral loss of heterozygosity mCAs. Our mCA fitness estimates, derived by aggregating per-individual PACER scores, were correlated (R2 = 0.49) with an alternative approach that estimated fitness of mCAs in the UK Biobank using population-level distributions of clonal fraction. Among individuals with JAK2 V617F clonal hematopoiesis of indeterminate potential or mCAs affecting the JAK2 gene on chromosome 9, PACER score was strongly correlated with erythrocyte count. In a cross-sectional analysis, genome-wide association study of estimates of mCA expansion rate identified a TCL1A locus variant associated with mCA clonal expansion rate, with suggestive variants in NRIP1 and TERT.

Association analysis between an epigenetic risk score and blood pressure.

Background: Epigenome-wide association studies have revealed multiple DNA methylation sites (CpGs) associated with alcohol consumption, an important lifestyle risk factor for cardiovascular diseases. Results: We generated an alcohol consumption epigenetic risk score (ERS) based on previously reported 144 alcohol-associated CpGs and examined the association of the ERS with systolic blood pressure (SBP), diastolic blood pressure (DBP), and hypertension (HTN) in 3,898 Framingham Heart Study (FHS) participants. We found an association of alcohol intake with the ERS in the meta-analysis with 0.09 units higher ERS per drink consumed per day (p < 0.0001). Cross-sectional analyses in FHS revealed that a one-unit increment of the ERS was associated with 1.93 mm Hg higher SBP (p = 4.64E-07), 0.68 mm Hg higher DBP (p = 0.006), and an odds ratio of 1.78 for HTN (p < 2E-16). Meta-analysis of the cross-sectional association of the ERS with BP traits in eight independent external cohorts (n = 11,544) showed similar relationships with blood pressure levels, i.e., a one-unit increase in ERS was associated with 0.74 (p = 0.002) and 0.50 (p = 0.0006) mm Hg higher SBP and DBP, but could not confirm the association with hypertension. Longitudinal analyses in FHS (n = 3,260) and five independent external cohorts (n = 4,021) showed that the baseline ERS was not associated with a change in blood pressure over time or with incident HTN. Conclusions: Our findings provide proof-of-concept that utilizing an ERS is a useful approach to capture the recent health consequences of lifestyle behaviors such as alcohol consumption.

Staying on track - Keeping things running in a high-end scientific imaging core facility.

Modern life science research is a collaborative effort. Few research groups can single-handedly support the necessary equipment, expertise and personnel needed for the ever-expanding portfolio of technologies that are required across multiple disciplines in today's life science endeavours. Thus, research institutes are increasingly setting up scientific core facilities to provide access and specialised support for cutting-edge technologies. Maintaining the momentum needed to carry out leading research while ensuring high-quality daily operations is an ongoing challenge, regardless of the resources allocated to establish such facilities. Here, we outline and discuss the range of activities required to keep things running once a scientific imaging core facility has been established. These include managing a wide range of equipment and users, handling repairs and service contracts, planning for equipment upgrades, renewals, or decommissioning, and continuously upskilling while balancing innovation and consolidation.

AI-enabled cardiac chambers volumetry in coronary artery calcium scans (AI-CACTM) predicts heart failure and outperforms NT-proBNP: The multi-ethnic study of Atherosclerosis.

INTRODUCTION: Coronary artery calcium (CAC) scans contain useful information beyond the Agatston CAC score that is not currently reported. We recently reported that artificial intelligence (AI)-enabled cardiac chambers volumetry in CAC scans (AI-CAC™) predicted incident atrial fibrillation in the Multi-Ethnic Study of Atherosclerosis (MESA). In this study, we investigated the performance of AI-CAC cardiac chambers for prediction of incident heart failure (HF). METHODS: We applied AI-CAC to 5750 CAC scans of asymptomatic individuals (52% female, White 40%, Black 26%, Hispanic 22% Chinese 12%) free of known cardiovascular disease at the MESA baseline examination (2000-2002). We used the 15-year outcomes data and compared the time-dependent area under the curve (AUC) of AI-CAC volumetry versus NT-proBNP, Agatston score, and 9 known clinical risk factors (age, gender, diabetes, current smoking, hypertension medication, systolic and diastolic blood pressure, LDL, HDL for predicting incident HF over 15 years. RESULTS: Over 15 years of follow-up, 256 HF events accrued. The time-dependent AUC [95% CI] at 15 years for predicting HF with AI-CAC all chambers volumetry (0.86 [0.82,0.91]) was significantly higher than NT-proBNP (0.74 [0.69, 0.77]) and Agatston score (0.71 [0.68, 0.78]) (p â€‹< â€‹0.0001), and comparable to clinical risk factors (0.85, p â€‹= â€‹0.4141). Category-free Net Reclassification Index (NRI) [95% CI] adding AI-CAC LV significantly improved on clinical risk factors (0.32 [0.16,0.41]), NT-proBNP (0.46 [0.33,0.58]), and Agatston score (0.71 [0.57,0.81]) for HF prediction at 15 years (p â€‹< â€‹0.0001). CONCLUSION: AI-CAC volumetry significantly outperformed NT-proBNP and the Agatston CAC score, and significantly improved the AUC and category-free NRI of clinical risk factors for incident HF prediction.

Enhancing selection of alcohol consumption-associated genes by random forest.

Machine learning methods have been used in identifying omics markers for a variety of phenotypes. We aimed to examine whether a supervised machine learning algorithm can improve identification of alcohol-associated transcriptomic markers. In this study, we analysed array-based, whole-blood derived expression data for 17 873 gene transcripts in 5508 Framingham Heart Study participants. By using the Boruta algorithm, a supervised random forest (RF)-based feature selection method, we selected twenty-five alcohol-associated transcripts. In a testing set (30 % of entire study participants), AUC (area under the receiver operating characteristics curve) of these twenty-five transcripts were 0·73, 0·69 and 0·66 for non-drinkers v. moderate drinkers, non-drinkers v. heavy drinkers and moderate drinkers v. heavy drinkers, respectively. The AUC of the selected transcripts by the Boruta method were comparable to those identified using conventional linear regression models, for example, AUC of 1958 transcripts identified by conventional linear regression models (false discovery rate < 0·2) were 0·74, 0·66 and 0·65, respectively. With Bonferroni correction for the twenty-five Boruta method-selected transcripts and three CVD risk factors (i.e. at P < 6·7e-4), we observed thirteen transcripts were associated with obesity, three transcripts with type 2 diabetes and one transcript with hypertension. For example, we observed that alcohol consumption was inversely associated with the expression of DOCK4, IL4R, and SORT1, and DOCK4 and SORT1 were positively associated with obesity, and IL4R was inversely associated with hypertension. In conclusion, using a supervised machine learning method, the RF-based Boruta algorithm, we identified novel alcohol-associated gene transcripts.

Methylation patterns associated with C-reactive protein in racially and ethnically diverse populations.

Systemic low-grade inflammation is a feature of chronic disease. C-reactive protein (CRP) is a common biomarker of inflammation and used as an indicator of disease risk; however, the role of inflammation in disease is not completely understood. Methylation is an epigenetic modification in the DNA which plays a pivotal role in gene expression. In this study we evaluated differential DNA methylation patterns associated with blood CRP level to elucidate biological pathways and genetic regulatory mechanisms to improve the understanding of chronic inflammation. The racially and ethnically diverse participants in this study were included as 50% White, 41% Black or African American, 7% Hispanic or Latino/a, and 2% Native Hawaiian, Asian American, American Indian, or Alaska Native (total n = 13,433) individuals. We replicated 113 CpG sites from 87 unique loci, of which five were novel (CADM3, NALCN, NLRC5, ZNF792, and cg03282312), across a discovery set of 1,150 CpG sites associated with CRP level (p < 1.2E-7). The downstream pathways affected by DNA methylation included the identification of IFI16 and IRF7 CpG-gene transcript pairs which contributed to the innate immune response gene enrichment pathway along with NLRC5, NOD2, and AIM2. Gene enrichment analysis also identified the nuclear factor-kappaB transcription pathway. Using two-sample Mendelian randomization (MR) we inferred methylation at three CpG sites as causal for CRP levels using both White and Black or African American MR instrument variables. Overall, we identified novel CpG sites and gene transcripts that could be valuable in understanding the specific cellular processes and pathogenic mechanisms involved in inflammation.

Protein kinase C activity modulates nuclear Lamin A/C dynamics in HeLa cells.

The nuclear lamina serves important functions in the nucleus, providing structural support to the nuclear envelope and contributing to chromatin organization. The primary proteins that constitute the lamina are nuclear lamins whose functions are impacted by post-translational modifications, including phosphorylation by protein kinase C (PKC). While PKC-mediated lamin phosphorylation is important for nuclear envelope breakdown during mitosis, less is known about interphase roles for PKC in regulating nuclear structure. Here we show that overexpression of PKC ß, but not PKC α, increases the Lamin A/C mobile fraction in the nuclear envelope in HeLa cells without changing the overall structure of Lamin A/C and Lamin B1 within the nuclear lamina. Conversely, knockdown of PKC ß, but not PKC α, reduces the Lamin A/C mobile fraction. Thus, we demonstrate an isoform-specific role for PKC in regulating interphase Lamin A/C dynamics outside of mitosis.

Association analysis between an epigenetic alcohol risk score and blood pressure.

Background: Epigenome-wide association studies have revealed multiple DNA methylation sites (CpGs) associated with alcohol consumption, an important lifestyle risk factor for cardiovascular diseases. Results: We generated an alcohol consumption epigenetic risk score (ERS) based on previously reported 144 alcohol-associated CpGs and examined the association of the ERS with systolic blood pressure (SBP), diastolic blood pressure (DBP), and hypertension (HTN) in 3,898 Framingham Heart Study (FHS) participants. We found an association of alcohol intake with the ERS in the meta-analysis with 0.09 units higher ERS per drink consumed per day (p < 0.0001). Cross-sectional analyses in FHS revealed that a one-unit increment of the ERS was associated with 1.93 mm Hg higher SBP (p = 4.64E-07), 0.68 mm Hg higher DBP (p = 0.006), and an odds ratio of 1.78 for HTN (p < 2E-16). Meta-analysis of the cross-sectional association of the ERS with BP traits in eight independent external cohorts (n = 11,544) showed similar relationships with blood pressure levels, i.e., a one-unit increase in ERS was associated with 0.74 (p = 0.002) and 0.50 (p = 0.0006) mm Hg higher SBP and DBP, but could not confirm the association with hypertension. Longitudinal analyses in FHS (n = 3,260) and five independent external cohorts (n = 4,021) showed that the baseline ERS was not associated with a change in blood pressure over time or with incident HTN. Conclusions: Our findings provide proof-of-concept that utilizing an ERS is a useful approach to capture the recent health consequences of lifestyle behaviors such as alcohol consumption.

Estimation of inbreeding and kinship coefficients via latent identity-by-descent states.

MOTIVATION: Estimating the individual inbreeding coefficient and pairwise kinship is an important problem in human genetics (e.g. in disease mapping) and in animal and plant genetics (e.g. inbreeding design). Existing methods, such as sample correlation-based genetic relationship matrix, KING, and UKin, are either biased, or not able to estimate inbreeding coefficients, or produce a large proportion of negative estimates that are difficult to interpret. This limitation of existing methods is partly due to failure to explicitly model inbreeding. Since all humans are inbred to various degrees by virtue of shared ancestries, it is prudent to account for inbreeding when inferring kinship between individuals. RESULTS: We present "Kindred," an approach that estimates inbreeding and kinship by modeling latent identity-by-descent states that accounts for all possible allele sharing-including inbreeding-between two individuals. Kindred used non-negative least squares method to fit the model, which not only increases computation efficiency compared to the maximum likelihood method, but also guarantees non-negativity of the kinship estimates. Through simulation, we demonstrate the high accuracy and non-negativity of kinship estimates by Kindred. By selecting a subset of SNPs that are similar in allele frequencies across different continental populations, Kindred can accurately estimate kinship between admixed samples. In addition, we demonstrate that the realized kinship matrix estimated by Kindred is effective in reducing genomic control values via linear mixed model in genome-wide association studies. Finally, we demonstrate that Kindred produces sensible heritability estimates on an Australian height dataset. AVAILABILITY AND IMPLEMENTATION: Kindred is implemented in C with multi-threading. It takes vcf file or stream as input and works seamlessly with bcftools. Kindred is freely available at https://github.com/haplotype/kindred.

Frontal midline theta transcranial alternating current stimulation enhances early consolidation of episodic memory.

Evidence implicating theta rhythms in declarative memory encoding and retrieval, together with the notion that both retrieval and consolidation involve memory reinstatement or replay, suggests that post-learning theta rhythm modulation can promote early consolidation of newly formed memories. Building on earlier work employing theta neurofeedback, we examined whether theta-frequency transcranial alternating stimulation (tACS) can engender effective consolidation of newly formed episodic memories, compared with beta frequency stimulation or sham control conditions. We compared midline frontal and posterior parietal theta stimulation montages and examined whether benefits to memory of theta upregulation are attributable to consolidation rather than to retrieval processes by using a washout period to eliminate tACS after-effects between stimulation and memory assessment. Four groups of participants viewed object pictures followed by a free recall test during three study-test cycles. They then engaged in tACS (frontal theta montage/parietal theta montage/frontal beta montage/sham) for a period of 20 min, followed by a 2-h break. Free recall assessments were conducted after the break, 24 h later, and 7 days later. Frontal midline theta-tACS induced significant off-line retrieval gains at all assessment time points relative to all other conditions. This indicates that theta upregulation provides optimal conditions for the consolidation of episodic memory, independent of mental-state strategies.

Cool-contacts: Cryo-Electron Microscopy of Membrane Contact Sites and Their Components.

Electron microscopy has played a pivotal role in elucidating the ultrastructure of membrane contact sites between cellular organelles. The advent of cryo-electron microscopy has ushered in the ability to determine atomic models of constituent proteins or protein complexes within sites of membrane contact through single particle analysis. Furthermore, it enables the visualization of the three-dimensional architecture of membrane contact sites, encompassing numerous copies of proteins, whether in vitro reconstituted or directly observed in situ using cryo-electron tomography. Nevertheless, there exists a scarcity of cryo-electron microscopy studies focused on the site of membrane contact and their constitutive proteins. This review provides an overview of the contributions made by cryo-electron microscopy to our understanding of membrane contact sites, outlines the associated limitations, and explores prospects in this field.

Targeted Proteomics Reveals Functional Targets for Early Diabetes Susceptibility in Young Adults.

BACKGROUND: The circulating proteome may encode early pathways of diabetes susceptibility in young adults for surveillance and intervention. Here, we define proteomic correlates of tissue phenotypes and diabetes in young adults. METHODS: We used penalized models and principal components analysis to generate parsimonious proteomic signatures of diabetes susceptibility based on phenotypes and on diabetes diagnosis across 184 proteins in >2000 young adults in the CARDIA (Coronary Artery Risk Development in Young Adults study; mean age, 32 years; 44% women; 43% Black; mean body mass index, 25.6±4.9 kg/m2), with validation against diabetes in >1800 individuals in the FHS (Framingham Heart Study) and WHI (Women's Health Initiative). RESULTS: In 184 proteins in >2000 young adults in CARDIA, we identified 2 proteotypes of diabetes susceptibility-a proinflammatory fat proteotype (visceral fat, liver fat, inflammatory biomarkers) and a muscularity proteotype (muscle mass), linked to diabetes in CARDIA and WHI/FHS. These proteotypes specified broad mechanisms of early diabetes pathogenesis, including transorgan communication, hepatic and skeletal muscle stress responses, vascular inflammation and hemostasis, fibrosis, and renal injury. Using human adipose tissue single cell/nuclear RNA-seq, we demonstrate expression at transcriptional level for implicated proteins across adipocytes and nonadipocyte cell types (eg, fibroadipogenic precursors, immune and vascular cells). Using functional assays in human adipose tissue, we demonstrate the association of expression of genes encoding these implicated proteins with adipose tissue metabolism, inflammation, and insulin resistance. CONCLUSIONS: A multifaceted discovery effort uniting proteomics, underlying clinical susceptibility phenotypes, and tissue expression patterns may uncover potentially novel functional biomarkers of early diabetes susceptibility in young adults for future mechanistic evaluation.

Manipulation of Embryonic Cleavage Geometry Using Magnetic Tweezers.

The geometry of reductive divisions that mark the development of early embryos instructs cell fates, sizes, and positions, by mechanisms that remain unclear. In that context, new methods to mechanically manipulate these divisions are starting to emerge in different model systems. These are key to develop future innovative approaches and understand developmental mechanisms controlled by cleavage geometry. In particular, how cell cycle pace is regulated in rapidly reducing blastomeres and how fate diversity can arise from blastomere size and position within embryos are fundamental questions that remain at the heart of ongoing research. In this chapter, we provide a detailed protocol to assemble and use magnetic tweezers in the sea urchin model and generate spatially controlled asymmetric and oriented divisions during early embryonic development.

A naturally occurring variant of SHLP2 is a protective factor in Parkinson's disease.

Mitochondrial DNA single nucleotide polymorphisms (mtSNPs) have been associated with a reduced risk of developing Parkinson's disease (PD), yet the underlying mechanisms remain elusive. In this study, we investigate the functional role of a PD-associated mtSNP that impacts the mitochondrial-derived peptide (MDP) Small Humanin-like Peptide 2 (SHLP2). We identify m.2158 T > C, a mtSNP associated with reduced PD risk, within the small open reading frame encoding SHLP2. This mtSNP results in an alternative form of SHLP2 (lysine 4 replaced with arginine; K4R). Using targeted mass spectrometry, we detect specific tryptic fragments of SHLP2 in neuronal cells and demonstrate its binding to mitochondrial complex 1. Notably, we observe that the K4R variant, associated with reduced PD risk, exhibits increased stability compared to WT SHLP2. Additionally, both WT and K4R SHLP2 show enhanced protection against mitochondrial dysfunction in in vitro experiments and confer protection against a PD-inducing toxin, a mitochondrial complex 1 inhibitor, in a mouse model. This study sheds light on the functional consequences of the m.2158 T > C mtSNP on SHLP2 and provides insights into the potential mechanisms by which this mtSNP may reduce the risk of PD.

Intentional forgetting needs intentional remembering.

Episodic memories may become suppressed, both incidentally and intentionally. Incidental suppression is a result of a competition induced by interfering items or responses. In contrast, intentional suppression is said to result from conscious attempts to suppress certain memory items, and should thus not depend on competition induced by interfering items or responses. However, intentional suppression is typically engendered using the Think/No-Think paradigm, in which participants are required to retrieve some target items and to suppress others. Therefore, rather than intentional suppression, forgetting in this paradigm may reflect incidental suppression of No-Think items induced by interference via prior retrieval of the Think items. To distinguish between these possibilities, we tested participants (n = 40) using an adjusted suppression paradigm, which did not include the Think condition (ExcludeThink paradigm) and compared it with the standard suppression paradigm (IncludeThink paradigm; n = 39) which included a think condition. We found that suppression was not observed in the ExcludeThink paradigm, but only in the IncludeThink paradigm. These results indicate that interference via prior retrieval is necessary to induce forgetting. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Development and Validation of a Protein Risk Score for Mortality in Heart Failure : A Community Cohort Study.

BACKGROUND: Heart failure (HF) is a complex clinical syndrome with high mortality. Current risk stratification approaches lack precision. High-throughput proteomics could improve risk prediction. Its use in clinical practice to guide the management of patients with HF depends on validation and evidence of clinical benefit. OBJECTIVE: To develop and validate a protein risk score for mortality in patients with HF. DESIGN: Community-based cohort. SETTING: Southeast Minnesota. PARTICIPANTS: Patients with HF enrolled between 2003 and 2012 and followed through 2021. MEASUREMENTS: A total of 7289 plasma proteins in 1351 patients with HF were measured using the SomaScan Assay (SomaLogic). A protein risk score was derived using least absolute shrinkage and selection operator regression and temporal validation in patients enrolled between 2003 and 2007 (development cohort) and 2008 and 2012 (validation cohort). Multivariable Cox regression was used to examine the association between the protein risk score and mortality. The performance of the protein risk score to predict 5-year mortality risk was assessed using calibration plots, decision curves, and relative utility analyses and compared with a clinical model, including the Meta-Analysis Global Group in Chronic Heart Failure mortality risk score and N-terminal pro-B-type natriuretic peptide. RESULTS: The development (n = 855; median age, 78 years; 50% women; 29% with ejection fraction <40%) and validation cohorts (n = 496; median age, 76 years; 45% women; 33% with ejection fraction <40%) were mostly similar. In the development cohort, 38 unique proteins were selected for the protein risk score. Independent of ejection fraction, the protein risk score demonstrated good calibration, reclassified mortality risk particularly at the extremes of the risk distribution, and showed greater clinical utility compared with the clinical model. LIMITATION: Participants were predominantly of European ancestry, potentially limiting the generalizability of the findings to different patient populations. CONCLUSION: Validation of the protein risk score demonstrated good calibration and evidence of predicted benefits to stratify the risk for death in HF superior to that of clinical methods. Further studies are needed to prospectively evaluate the score's performance in diverse populations and determine risk thresholds for interventions. PRIMARY FUNDING SOURCE: Division of Intramural Research at the National Heart, Lung, and Blood Institute of the National Institutes of Health.

Extracellular vesicles as therapeutics for inflammation and infection.

Extracellular vesicles (EVs) are an emergent next-generation biotechnology with broad application potential. In particular, immunomodulatory bioactivity of EVs leading to anti-inflammatory effects is well-characterized. Cell source and culture conditions are critical determinants of EV therapeutic efficacy, while augmenting EV anti-inflammatory bioactivity via diverse strategies, including RNA cargo loading and protein surface display, has proven effective. Yet, translational challenges remain. Additionally, the potential of direct antimicrobial EV functionality has only recently emerged but offers the possibility of overcoming drug-resistant bacterial and fungal infections through novel, multifactorial mechanisms. As discussed herein, these application areas are brought together by the potential for synergistic benefit from technological developments related to EV cargo loading and biomanufacturing.

Proteomics for heart failure risk stratification: a systematic review.

BACKGROUND: Heart failure (HF) is a complex clinical syndrome with persistently high mortality. High-throughput proteomic technologies offer new opportunities to improve HF risk stratification, but their contribution remains to be clearly defined. We aimed to systematically review prognostic studies using high-throughput proteomics to identify protein signatures associated with HF mortality. METHODS: We searched four databases and two clinical trial registries for articles published from 2012 to 2023. HF proteomics studies measuring high numbers of proteins using aptamer or antibody-based affinity platforms on human plasma or serum with outcomes of all-cause or cardiovascular death were included. Two reviewers independently screened articles, extracted data, and assessed the risk of bias. A third reviewer resolved conflicts. We assessed the risk of bias using the Risk Of Bias In Non-randomized Studies-of Exposure tool. RESULTS: Out of 5131 unique articles identified, nine articles were included in the review. The nine studies were observational; three used the aptamer platform, and six used the antibody platform. We found considerable heterogeneity across studies in measurement panels, HF definitions, ejection fraction categorization, follow-up duration, and outcome definitions, and a lack of risk estimates for most protein associations. Hence, we proceeded with a systematic review rather than a meta-analysis. In two comparable aptamer studies in patients with HF with reduced ejection fraction, 21 proteins were identified in common for the association with all-cause death. Among these, one protein, WAP four-disulfide core domain protein 2 was also reported in an antibody study on HFrEF and for the association with CV death. We proposed standardized reporting criteria to facilitate the interpretation of future studies. CONCLUSIONS: In this systematic review of nine studies evaluating the association of proteomics with mortality in HF, we identified a limited number of proteins common across several studies. Heterogeneity across studies compromised drawing broad inferences, underscoring the importance of standardized approaches to reporting.

Association analysis of mitochondrial DNA heteroplasmic variants: methods and application.

We rigorously assessed a comprehensive association testing framework for heteroplasmy, employing both simulated and real-world data. This framework employed a variant allele fraction (VAF) threshold and harnessed multiple gene-based tests for robust identification and association testing of heteroplasmy. Our simulation studies demonstrated that gene-based tests maintained an appropriate type I error rate at α=0.001. Notably, when 5% or more heteroplasmic variants within a target region were linked to an outcome, burden-extension tests (including the adaptive burden test, variable threshold burden test, and z-score weighting burden test) outperformed the sequence kernel association test (SKAT) and the original burden test. Applying this framework, we conducted association analyses on whole-blood derived heteroplasmy in 17,507 individuals of African and European ancestries (31% of African Ancestry, mean age of 62, with 58% women) with whole genome sequencing data. We performed both cohort- and ancestry-specific association analyses, followed by meta-analysis on both pooled samples and within each ancestry group. Our results suggest that mtDNA-encoded genes/regions are likely to exhibit varying rates in somatic aging, with the notably strong associations observed between heteroplasmy in the RNR1 and RNR2 genes (p<0.001) and advance aging by the Original Burden test. In contrast, SKAT identified significant associations (p<0.001) between diabetes and the aggregated effects of heteroplasmy in several protein-coding genes. Further research is warranted to validate these findings. In summary, our proposed statistical framework represents a valuable tool for facilitating association testing of heteroplasmy with disease traits in large human populations.