Publications by authors named "Halama A"

The steroid hormone progesterone (P4) regulates multiple aspects of reproductive and metabolic physiology. Classical P4 signaling operates through nuclear receptors that regulate transcription. In addition, P4 signals through membrane P4 receptors (mPRs) in a rapid nongenomic modality.

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Recent advances in high-throughput measurement technologies have enabled the analysis of molecular perturbations associated with disease phenotypes at the multi-omic level. Such perturbations can range in scale from fluctuations of individual molecules to entire biological pathways. Data-driven clustering algorithms have long been used to group interactions into interpretable functional modules; however, these modules are typically constrained to a fixed size or statistical cutoff.

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  • This study integrates 18 advanced omics technologies using samples from 391 participants to analyze complex physiological processes and pathologies related to diabetes.* -
  • With over 6,000 molecular traits and various genetic and epigenetic factors, the research establishes a comprehensive molecular network showcasing significant correlations between different traits in biological fluids.* -
  • The findings not only shed light on diabetes subtypes but also provide an open-access web interface for users to explore the molecular data and generate new hypotheses.*
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  • Immunoglobulin (Ig) glycosylation significantly influences immune responses and is crucial in aging and diseases, but research has primarily focused on IgG, leaving IgA glycosylation less understood.
  • Using a new liquid chromatography-mass spectrometry method, researchers created a large dataset of IgA glycosylation from 2423 twin serum samples, identifying key N- and O-glycan species.
  • The findings reveal that IgA glycosylation is highly heritable, varies with sex and age, and is largely influenced by shared genetic factors, with specific genetic loci associated with IgA and IgG glycomes linked to immune disease risk, including IgA nephropathy.
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  • GWAS utilizing mass spectrometry-based proteomics (MS) are vital for drug discovery, addressing limitations of traditional affinity proteomics that restrict analysis to specific protein panels.
  • The study analyzed blood samples from 1,260 Americans and 325 individuals from Asia, identifying 252 pQTLs—90 of which were replicated, including 30 previously unreported variants.
  • Results showed that about one-third of affinity proteomics pQTLs may be influenced by epitope effects, demonstrating the need for diverse proteomics techniques to uncover previously inaccessible pQTLs.
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  • Proteogenomics research focuses on generating hypotheses about protein function and identifying potential drug targets, previously relying heavily on affinity-based proteomics, which has limitations such as non-specific binding and variant handling.* -
  • The study utilizes a mass spectrometry-based proteomics approach with the Proteograph™ Product Suite, enabling the analysis of over 18,000 unique peptides from nearly 3,000 proteins in more than 320 diverse blood samples.* -
  • Findings include the identification of 184 protein-altering variants in 137 genes that are strongly linked to their respective peptides, which enhances the understanding of protein specificity and offers support for potential drug targets in the bloodstream.*
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Background: Bardet-Biedl syndrome (BBS) is an autosomal recessive, genetically heterogeneous, pleiotropic disorder caused by variants in genes involved in the function of the primary cilium. We have harnessed genomics to identify BBS and ophthalmic technologies to describe novel features of BBS.

Case Presentation: A patient with an unclear diagnosis of syndromic type 2 diabetes mellitus, another affected sibling and unaffected siblings and parents were sequenced using DNA extracted from saliva samples.

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The steroid hormone progesterone (P4) regulates multiple aspects of reproductive and metabolic physiology. Classical P4 signaling operates through nuclear receptors that regulate transcription. In addition, P4 signals through membrane P4 receptors (mPRs) in a rapid nongenomic modality.

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One of the most essential health problems is cancer, the first or second cause of death worldwide. Head and neck cancers are hard to detect due to non-specific symptoms. The treatment often relies on a combination of radio and chemotherapy.

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  • Human plasma proteins are crucial as clinical biomarkers and potential drug targets, and studying their genetic variants can help us understand their abundance.
  • The study conducted a meta-analysis across nearly 23,000 individuals to identify genetic variants associated with 92 plasma proteins linked to cardiometabolic conditions, discovering 503 significant variants.
  • Notably, sex differences were observed in 23.5% of the identified variants, and further analysis suggested causal links between certain proteins and various health traits, providing insight into their roles in cardiometabolic diseases.
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  • Exercise-induced hemolysis in endurance racehorses is linked to intense exercise, resulting from factors like repeated muscle contractions and foot strikes, which compress capillaries and affect blood flow.
  • A study involving 47 Arabian horses covering varying distances revealed significant increases in hemolysis parameters post-race, indicating a correlation with exercise intensity and performance outcomes.
  • By using advanced metabolomics techniques alongside traditional methods, the research highlighted the importance of considering metabolic health and individual horse limitations to prevent serious injuries related to excessive strain during races.
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Cancer cells frequently undergo metabolic reprogramming as a mechanism of resistance against chemotherapeutic drugs. Metabolomic profiling provides a direct readout of metabolic changes and can thus be used to identify these tumor escape mechanisms. Here, we introduce piTracer, a computational tool that uses multi-scale molecular networks to identify potential combination therapies from pre- and post-treatment metabolomics data.

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  • Type 2 diabetes (T2D) has different causes and effects, which influence how it develops and is treated.
  • A study identified four subtypes of T2D: severe insulin deficient (SIDD), severe insulin resistant (SIRD), mild obesity-related (MOD), and mild age-related (MARD) diabetes.
  • The research also applied a clustering approach to the Qatar Biobank and found unique molecular profiles for each subtype, helping to better understand their specific biological mechanisms.
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Small non-coding RNAs, known as microRNAs (miRNAs), have emerging regulatory functions within the ovary that have been related to fertility. This study was undertaken to determine if circulating miRNAs reflect the changes associated with the parameters of embryo development and fertilization. In this cross-sectional pilot study.

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Genome-wide association studies (GWAS) with non-targeted metabolomics have identified many genetic loci of biomedical interest. However, metabolites with a high degree of missingness, such as drug metabolites and xenobiotics, are often excluded from such studies due to a lack of statistical power and higher uncertainty in their quantification. Here we propose ratios between related drug metabolites as GWAS phenotypes that can drastically increase power to detect genetic associations between pairs of biochemically related molecules.

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Modern metabolomics platforms are able to identify many drug-related metabolites in blood samples. Applied to population-based biobank studies, the detection of drug metabolites can then be used as a proxy for medication use or serve as a validation tool for questionnaire-based health assessments. However, it is not clear how well detection of drug metabolites in blood samples matches information on self-reported medication provided by study participants.

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Tumor growth and metastasis strongly depend on adapted cell metabolism. Cancer cells adjust their metabolic program to their specific energy needs and in response to an often challenging tumor microenvironment. Glutamine metabolism is one of the metabolic pathways that can be successfully targeted in cancer treatment.

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Metastasis is the primary cause of cancer related deaths due to the limited number of efficient druggable targets. Signatures of dysregulated cancer metabolism could serve as a roadmap for the determination of new treatment strategies. However, the metabolic signatures of metastatic cells remain vastly elusive.

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Kidney transplantation is the treatment of choice for patients with end-stage kidney failure, but transplanted allograft could be affected by viral and bacterial infections and by immune rejection. The standard test for the diagnosis of acute pathologies in kidney transplants is kidney biopsy. However, noninvasive tests would be desirable.

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Equine performance in endurance racing depends on the interplay between physiological and metabolic processes. However, there is currently no parameter for estimating the readiness of animals for competition. Our objectives were to provide an in-depth characterization of metabolic consequences of endurance racing and to establish a metabolic performance profile for those animals.

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Metabolic pathways that are corrupted at early stages of insulin resistance (IR) remain elusive. This study investigates changes in body metabolism in clinically healthy and otherwise asymptomatic subjects that may become apparent already under compromised insulin sensitivity (IS) and prior to IR. 47 clinically healthy Arab male subjects with a broad range of IS, determined by hyperinsulinemic-euglycemic clamp (HIEC), were investigated.

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Post-transcriptional modification of RNA (RNA editing, RNAe) results in differences between the RNA transcript and the genomic DNA sequence (RDD). Enzymatic modification of adenosine to inosine (A2I) by ADAR is the most studied type of RNAe. However, few genetic association studies with A2I RNAe events have been conducted.

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Background: Dysregulated cancer metabolism is associated with acquired resistance to chemotherapeutic treatment and contributes to the activation of cancer survival mechanisms. However, which metabolic pathways are activated following treatment often remains elusive. The combination of chicken embryo tumor models () with metabolomics phenotyping could offer a robust platform for drug testing.

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